MCN 2026

Museums have produced video and media for decades—but what does it mean to design media that sustains voice over time?


In an era shaped by AI-generated content, rapid platform change, and evolving expectations around access, the question is no longer only how voice is captured. It is also how voice is mediated, translated, maintained, and trusted. This session examines how digital systems and human processes shape how museums represent the voices of artists, people, and communities.


While many institutions create subject-based videos, these projects are often treated as one-off assets tied to a specific exhibition or platform. This case study reframes media as infrastructure: a network of decisions across production, interviewing, editing, captioning, interface design, playback, and maintenance. Together, these decisions determine how voice is experienced, accessed, and understood.


Drawing from Crystal Bridges Museum of American Art’s Artist Voices video series, developed as part of the museum’s 2026 expansion reinstallation, this session explores how museums can design media systems that preserve the integrity of voice across in-gallery video stations, web platforms, social media, and future reuse. The series focuses on living artists, where voice is collaborative but shaped through many stages of production. Interviewing, editing, pacing, translation, captioning, and platform design all influence what is shared, emphasized, and sustained.


The session will give particular attention to the representation of Indigenous voices within artist-centered media, including mini-documentaries featuring artists Nicholas Galanin and Lily Hope. In this context, sustaining voice requires more than recording an interview or presenting an artist’s words. It requires attention to agency, authorship, cultural specificity, and how institutional editing can either preserve complexity or unintentionally flatten it. The framing of questions, filming relationships, and edit decisions all shape how Indigenous perspectives are carried forward.


A video may begin as a conversation, but it reaches audiences through layers of editing, translation, accessibility, design, and institutional decision-making. These choices shape meaning, access, and trust.


The session will also address practical decisions that support sustainability, including dual-language open captions, standardized media formats, multi-platform design, consistent playback, and coordination between content, design, technology, and installation teams. These choices show how accessibility, consistency, and technical planning are essential components of ethical digital interpretation.


Attendees will leave with strategies for designing digital media as durable systems rather than isolated outputs, with approaches for balancing authenticity, accessibility, longevity, and audience trust.

The National Museum of the American Indian (NMAI) is defined by its relationship to the communities and people who are connected to the museum’s collection. Though the museum’s collection of Native items is the largest in the world and contains many artistic and cultural masterpieces, we strive to let visitors to our museum understand that each of these items is a starting point to cultural understanding. As a museum of living cultural history, the NMAI has unique challenges to meet our visitors where they are, provide an engaging experience and to help develop new understandings about Native peoples. We hope to have visitors think about the museum as defined by a collection of relationships as much as a collection of items.

In this short presentation, Daniel Davis and Melissa Shaginoff will present their work on the Welcome Media project that seeks to highlight the diversity, hemispheric scope and most importantly the centrality of collaborative relationships that are necessary to build the trust with Native communities who teach us how to present their culture and to care for the items in our collection. The Welcome Media project is a series of short films that will show daily at our museum in Washington DC and in New York beginning in the fall of 2026. The films were designed to be interchangeable allowing the museum to add additional stories to the cycle in the future. Through findings from an ongoing visitor study by HG and Co, we learned that most visitors appreciated knowing more about the Museum’s relationship with Native communities. The study found that a few visitors expressed skepticism that these relationships were truly deep and authentic, and we feel the Welcome Media project should help to resolve these lingering doubts.

At a time when social media’s engagement obsession has made it feel like the truth no longer matters and the use of artificial intelligence has given rise to mistrust of science and expertise, this project will emphasize the real time commitment to building relationships with our Native and non-Native constituents. We believe that by showing how the museum works and allowing visitors to hear directly from contemporary Native people, visitors that experience our museums will have a greater trust and in what they learn during their visit. Further, by realigning visitor’s expectations and helping them to realize that they are part of a network of connection through the items they see on view, they can have a richer and more impactful experience that may change how they see Native people today.

In this presentation, we will present data from our visitor studies testing messages and understanding our visitor’s expectations, explain the development of a modular film cycle that can be revised and adjusted in the daily screenings, profile how the team made decisions about which communities to feature and show clips from the final media products.

This session will look at the Smithsonian Asian Pacific American Center (APAC)’s first 3D virtual tour as a case study for how museums can leverage technology to increase the longevity of short-term exhibitions while also enhancing the digital experience through community-centered interpretation and input.

In 2024, APAC opened its first exhibition in nearly 10 years called Sightlines: Chinatown and Beyond, curated by Sojin Kim with support from Adriel Luis and Mia Owens. Sightlines was open from September 2024 to November 2025 and focused on the impact Asian Americans had on the physical and cultural landscape of Washington, DC. 

The featured stories highlight examples of cultural production that interpret elements of Chinese, Korean, and Javanese heritage and express coalitional Asian American and BIPOC identities. These are presented in displays of artwork, material culture, images, and other graphic material drawn from Smithsonian collections as well as shared by local lenders, including community members and repositories such as the DC History Center and the Moorland-Spingarn Research Center at Howard University.

In order to preserve this exhibition in a dynamic and engaging way, we sought to create a self-guided 3D tour where visitors could explore the gallery as if they were physically there. To enhance their digital visit, the virtual exhibition was embedded with exclusive interviews from community members who loaned or had connections to objects shown in the exhibition. There are 27 individual audio clips throughout the virtual tour, full transcripts, and related resources for visitors to take a deeper dive into topics mentioned in the interviews. 

By attending this session, attendees will learn more about the overall exhibition, the internal discussions had to greenlight the 3D virtual tour, the design and technical decisions made to ensure longevity of the tour and exhibition integrity, and the community care necessary to ensure its success. There will be a brief portion at the end on how we've activated the virtual tour for educational purposes already and the reaction from community members, educators, and students. Lastly, there will be a sneak peak of our upcoming 3D Tour for APAC’s newest exhibition - How Can You Forget Me: Filipino American Stories.

Most AI-for-archives work in GLAM comes from engineers at vendor companies or well-resourced institutional AI teams. This session is a practitioner case study from a different corner: a public library manager — without an engineering background or an in-house AI team — building local-first AI infrastructure for a rights-sensitive regional broadcast archive.

The Northeast Ohio Broadcast Archives (NEOBA) are roughly 10,000–15,000 hours of regional broadcast footage. A digitized slice of 349 tapes from 1977–1982 served as the starting material. Cloud AI services were off the table — rights posture, institutional trust, and the sensitivity of local-community material all pointed to local-first processing, as did the budget and staffing reality of a public library.

Two artifacts will be demonstrated. The first is a local AI pipeline running on a single M-series Mac: scene detection, segment-level visual description (Gemma 4 E4B), transcription (mlx-whisper), face and entity detection (InsightFace), and Dublin-Core catalog synthesis (Gemma 4 26B A4B). The second is a public-facing Archive Explorer surfacing 14,242 classified items, 3,446 extracted entities, and 292 semantic clusters — with narrative threads and an AI-assisted chat interface for natural-language discovery that let someone unfamiliar with the collection begin exploring from any angle.

Both are examined honestly: what local-first bought in institutional trust, what it cost in throughput and fidelity, where contemporary AI tools extended what a small library team could do — and where they did not. The session also takes up a question the theme invites directly: as AI capability becomes cheaper and more locally runnable, who gets to build it, for whose collections, at whose institutions? A non-engineer practitioner working from a single workstation inside a public library is an unlikely builder profile for this work in 2026 — and that unlikelihood is part of the point.

Attendees leave with a reference implementation for local AI in a rights-sensitive archival setting, a set of trade-off conversations worth having before cloud-defaulting, and a practitioner perspective on AI-augmented work at institutions whose starting posture is not that of a cloud-first AI lab.

This session will provide an overview of the Museum of Modern Art’s implementation of new artificial intelligence tools in support of its access and accessibility priorities. The discussion will detail the decision-making involved in assessing and judiciously integrating AI into workflows, focusing on the identification and description of art assets. The presentation will recount three projects: identifying artworks in installation images; generating alt-text descriptions for images; and transcribing media assets with AI, as well as touching on available AI tools the Museum deemed as unsuitable or inappropriate for use.

This talk will address considerations applicable to other GLAM environments, from the specific challenges of working with a corpus of complex Modern Art material to assessing the suitability, accuracy, and resource expenditure involved in using artificial intelligence tools. The session will also detail the Museum-specific issues influencing the design and viability of the tools used, and consider the degree to which these models are replicable in other environments. In keeping with the conference's focus on Trust and Longevity, we will discuss the benefits of augmenting and repurposing Museum data to create a more expansive and trustworthy record of MoMA’s exhibition activity, and provide information for colleagues in the field weighing the costs and benefits of using AI in collections management.

This session would be well-suited for incorporation into a longer panel focused on institutional workflows, new platform adoption, or the experimental use of artificial intelligence tools in GLAM settings.

Museums have explored XR in different forms, from AR tours and VR exhibitions to immersive games, WebXR, and digital storytelling experiences. But many projects still struggle to move beyond novelty, short-term pilots, or one-time funding. For small and mid-sized institutions especially, the challenge is not simply adopting immersive technology, but choosing approaches that are meaningful to audiences, responsible to the stories being told, and sustainable for teams over time.

This session introduces a practical “XR pressure test” for evaluating museum XR ideas before major resources are committed. Adapted from cross-platform immersive learning work in cultural storytelling and education, the framework begins with a Spatial Necessity Test: what can audiences understand through embodied presence, participation, or spatial context that they could not understand as well through text, images, video, or a traditional website? From there, the talk expands into a series of planning questions around audience value, interpretive responsibility, accessibility, platform fit, maintenance, and long-term institutional capacity.

Using brief examples from social AR, VR learning environments, and AI-assisted production workflows, the session will show how museums can distinguish between XR concepts that are strategically justified and those driven mainly by novelty. It will also address common risks in museum XR planning, including platform dependency, unclear success metrics, limited accessibility, content that requires careful cultural context, and pilot projects that are exciting at launch but difficult to sustain.

Attendees will leave with a lightweight decision framework they can bring back to planning meetings, grant conversations, vendor discussions, or internal strategy sessions. A take-home “Museum XR Pressure Test Worksheet” will help teams decide whether an XR idea should be built, simplified, postponed, or reframed into a more sustainable format.

This summer, Crystal Bridges Museum of American Art launched the first version of its very own AI Companion App designed to help visitors identify works of art and have a rich conversation about what they’re seeing—all with artificial intelligence.

One major question we had to answer: can a conversational AI experience, even one designed in partnership with the museum’s curatorial staff, be trusted as a real-time visitor companion?

In this highly practical and engaging 45‑minute session, Stace Treat - Director of Interpretation - and Amanda Boomstra - Strategic advisor for museums - will share the product and institutional decisions required to make AI experiences trustworthy, deeply engaging, and built to scale beyond the current collection. Our starting point is always visitor value: we build what genuinely enhances the experience, not what simply showcases technology. 

We’ll cover the end-to-end approach: shaping a companion personality and conversation design that mirrors natural turns in human conversation; the challenges of grounding responses in legacy collections data; and designing accessible, inclusive interaction patterns that feel familiar to every user. Attendees will leave with clear takeaways for pairing data foundations, governance, and UX transparency to sustain trust in AI-driven interpretation over time.

As aquariums expand digital touchpoints across the guest journey, visitors expect fast, accurate access to information. At the Monterey Bay Aquarium, we introduced the Kelp Desk chatbot to help guests quickly find answers across our website. 

But deploying a chatbot isn’t just a technical issue; it’s a trust exercise. 

In this session, we’ll share what it takes to design, launch, and sustain a chatbot that supports the guest experience. We’ll cover how content quality impacts AI performance, what’s required to maintain accuracy over time, and how to manage a chatbot within existing resources. With real-life grounded lessons, this session focuses on both the opportunities and limitations of AI in a mission-driven environment. 

Attendees will leave with practical insight on how to implement and sustain a chatbot in a way that builds long-term trust with their digital audiences.

Trust is not built by content alone. It is built by the systems that shape how content is commissioned, interpreted, delivered, and sustained over time.

This case study examines Love in a Dangerous Time: Canada’s LGBT Purge, a major exhibition at the Canadian Museum for Human Rights and recipient of the 2026 Governor General’s Award for Excellence in Museums. The exhibition addresses one of the largest workplace human rights violations in Canadian history, telling the story of how more than 9,000 2SLGBTQI+ members of the Canadian Armed Forces, RCMP, and federal public service were investigated, harassed, and fired by the Canadian state.

As exhibition lead responsible for design and integration, I worked across artistic collaboration, survivor testimony, interaction design, and institutional systems to build an experience audiences could trust. That meant more than producing compelling media. It required aligning commissioned artworks, voice-driven interactives, accessible design protocols, and narrative architecture into a coherent framework that could hold trauma, complexity, and public scrutiny without collapsing into spectacle.

For MCN’s theme of Trust & Longevity, this session argues that trust in museum technology is inseparable from governance, accessibility, and care. Voice interfaces, immersive media, and artist-led commissions can deepen engagement, but only when supported by ethical decision-making, inclusive design, and infrastructure built for endurance rather than novelty.

Drawing on this project and related work in voice interaction, inclusive design, and enterprise digital governance, I will offer a practical framework for using technology to support difficult histories in ways that are credible now and sustainable over time.

You work with dozens of brilliant colleagues, all with amazing ideas about how technology might revolutionize your organization. You also want to sleep sometimes. How do you choose what to work on?  How do you prioritize?  How do you say no to the chief curator? 

At Getty, we’ve spent the past three years building a process to help us answer these questions and provide a framework for digital decision-making. We’d like to share with you the Digital Governance process we’ve put in place, what we’ve learned, and how we moved (at least closer) to transparent, inclusive, collaborative decision-making, and how we continue to evolve that process as organizational needs, technologies, and expectations evolve.  Also—AI governance! 

David Newbury and Britt Scholnick will share how we developed the framework, both from a strategic and practical level, how we’ve iterated over the past 18 months, and where we expect it to change in the future. We’ll discuss balancing IT and Digital needs, the value of discovery processes, how we consider capacity planning, and the importance of happy hours to team building.  And we’ll share how governance can function not (only) as a gatekeeping mechanism, but as a living system that supports sustainability, transparency, and builds institutional resilience.

In our museum, traditional wall interpretation provides the vital foundation of our guests’ experience. However, when planning our digital interpretation, our team is always asking: What can digital do that is different? This session explores creating “MTMDs” (Magical, Tactile Media Devices)—physical objects with digital content that guests interact with in ways that feel anything but digital. By focusing on what digital does best—recreating sensory "time and place"—we can provide a richer, more multi-dimensional experience.




Phase I: More Than Voiceover (William Gropper Exhibition)

Our exploration began by moving beyond the lecture-style audio tour. For an exhibition on William Gropper, we developed a "contextual soundscape" to sit alongside the curatorial text. By re-recording period-accurate union songs and dramatic re-enactments of Gropper’s appearance before the House Un-American Activities Committee, we provided the emotional high stakes of the period, allowing visitors to hear the history they were reading about.

Phase II: The Tactile Bridge (The Mucha Record Player)

We expanded this approach for our exhibition Timeless Mucha by introducing a custom hi-fi record player cabinet powered by RFID technology. This device allowed guests to listen to the music of albums whose cover art was inspired by Alphonse Mucha’s work. By using familiar, tactile hardware, we reduced placed the digital tech in the background, and put the guests tactile experience in the foreground. 

Phase III: Immersive Simulation (The Miró TV Time Capsule)

Our most recent project, a glowing 1950s television set for Miró and the United States, represents the synthesis of these strategies. To provide a unique experience of the 1940s–60s, we engaged a woodworker to build a period-accurate cabinet that matched the original furniture of our museum. On this TV, each channel represents a year Miró visited the U.S., allowing guests to "channel surf" through collages of cultural touchpoints like the Space Race and the Civil Rights Movement. Accompanied by a 1950s-style “TV Guide” handout, the interactive was placed in our Welcome Gallery to serve as an inflection point, drawing guests into the exhibition narrative the moment they enter the building.




Conclusion: Throwing Your Hat Over the Wall

Innovation in museum tech often requires "throwing your hat over a wall" that is too high to climb—committing to a project before you fully know how to execute it. These projects involved a multitude of firsts for our department and institution from programming Arduino boards to coding in Python and using Touch Designer. We argue that the most impactful museum experiences come from making mistakes and "building rockets to see if they explode". By diversifying the modes of interpretation we create an inclusive environment that recognizes the unique strengths of both the written word and the sensory interactive.

For an upcoming exhibition on the artist Piet Mondrian, MoMA is using digital technology to present conservation research that unfolds some of the major narratives and questions of the exhibition: how did Mondrian's migration to New York affect his art; why did he revise and double-date artworks that he had 'finished' in Europe; and what does it mean to make a painting, in his words, "more Boogie Woogie". This work has involved a number of creative challenges: Technical, very specific research findings need to be moulded into engaging narratives that can be appreciated by a broad range of audiences, satisfy different preferred learning modalities, and navigate areas where knowledge is theoretical and incomplete clearly. In an age rife with digital misinformation, it is especially important that museums speak to people effectively and confidently. This session will cover the creative and educational approaches we took to address these challenges and excavate for visitors another fascinating layer of Mondrian’s life and work.




We’ll also speak to some of the considerations from the design and technology perspective. Using AI-assisted rapid prototyping to minimize development time, creating reusable templates that are easy for content creators to deploy, building in flexibility in the form of modes and overrides that allow the interactive to serve the bespoke needs of particular narratives or exhibitions.




Though the Mondrian interactive is the star of this particular session, we’ll also speak to our broader effort to develop our suite of digital interactives - publications, chronologies, 3d views, geographic stories, music, conservation stories and more. We’re also looking into a system of lightweight experiences like trivia and treasure hunts made for special events. Our ultimate aim, like many of our peer institutions, is to be able to build a sustainable roster of digital interactives that can disseminate knowledge, delight visitors, and be adaptable enough to tell the many, many stories that need to be told at our museum in a sustainable way.

To commemorate the 250th anniversary of the Unites States, the central @Smithsonian social media team was tasked with creating 250 pieces of content with an emphasis on video. To meet this ambitious goal, they have been building new workflows across internal communications teams to tell stories across 21 museums, research centers, and the National Zoo.  

First, the team expanded beyond social media. The central Office of Public Affairs formed a working group that includes members of the marketing, press, social media, web, and 250 communications teams. Presenters will cover how responsibilities have been divided (and conquered) and how the strategy has been rolled out to garner internal buy-in across the institution.  

How do they tailor content to specific channels and platforms? In a multi-channel strategy where all channels matter, how do they handle internal competition? Who participates in the planning and editing process? How do they measure success? 

By diving into specific video series, presenters will explore these questions and share lessons learned.

In recent years there has been much productive discussion both at MCN and within institutions on AI-generated visual descriptions for accessibility: how to generate descriptions, how good they need to be, and how institutions should oversee their use. Some museums have already successfully released AI-generated descriptions as accessibility text. 

The Met has been treating AI-generated descriptions as something different: not (yet) as a final user-facing product, but as raw search material. With descriptions of what artworks depict, embedded into vector space and indexed alongside traditional metadata, one can build a discovery experience that works not only for experts, but also for the roughly two-thirds of users who arrive at our collection without a specific artwork in mind. Users searching for "year of the horse," "mythical beasts," or "eating food together" can find relevant works for the first time. Users searching in Chinese, Spanish, or any of dozens of languages can now find the same works as users searching in English. Users without art-historical vocabulary find what they are looking for without needing to know an artist's name or an artwork’s title. And yes, the search still works for our experts and researchers who search via fields like accession number.

We will share what we learned shipping this to a production system of The Met’s 550,000 objects used by millions of visitors a year. We will cover the technical pipeline (vision-language models, embeddings, hybrid lexical-and-semantic search), the evaluation problem (with different concerns when descriptions are an input to search rather than user-facing text), the UX work (in many ways more difficult than the engineering), and what our post-launch analytics and user feedback have actually shown. We will be candid about what worked, what surprised us, what still fails, and what we would do differently. We will also share what transfers to other institutions and what is specific to working at this scale.

This case study offers a closer look at this year’s wildly successful short-form Museum Rizzler video series, created by the National Gallery of Art’s social media team. We’ll discuss the right way to lean into a trend, balancing humor and art history, and the logistics of delivering content in a nimble and responsive way. The presentation will also address practical considerations including cross-team collaboration, approvals, production timelines, and risk assessment when participating in fast-moving online conversations. By sharing lessons learned, performance insights, and examples from the series, this session offers a framework for museums seeking to participate authentically in internet culture while maintaining institutional values and audience trust.

The brutal reality in 2026 is that there is scant effort being made in the cultural heritage sector to engage with generative systems outside of being simple consumers. Maybe one of the big vendors will give us discounted rates for a limited time and we can achieve "great things". At the end of the day though few, if any, organizations will be in a position to control their own destiny. Nor will they  have done anything to change the power dynamic of surviving on the benevolence of someone else's handouts. We simply don't have the knowledge, skills or means to deploy these systems and little to no collective work is happening right now to change that.

SFO Museum has been developing a suite of open source tools designed to run on consumer-grade hardware (even old and crusty hardware) for producing, storing, querying and visualizing vector embeddings using as many different open-weight large language models as possible. Specifically we are using vector embeddings to implement image similarity features for collections imagery and other image-based artifacts related to museum programming; to offer avenues of suggestion for investigating our various efforts derived from the properties "seen" by different ML models in the images of those works.

This idea of using vector embeddings to "bridge" different aspects of museum programming – collections imagery, photos posted to social media, exhibition and installation photos - has led SFO Museum to publish our vector embeddings for anyone else to use and to encourage the broader cultural heritage sector to do the same. Cross-institutional collections search continues to be something of a “holy grail” in museums and other cultural heritage institutions. Vector-based image similarity, while imperfect, offers a meaningful first step to finally achieve it. It is a messy, or at least fuzzy, solution and tilts more towards the “discovery and surprise” end of the spectrum rather than informed academic research. While it may not be a tool for scholars and experts, it can still provide meaningful avenues for non-experts to investigate and discover the relationship between different collections. This was still the stuff of fantasy a few years ago and now it is within our reach using nothing more than consumer-grade computer hardware.

This presentation will demonstrate the work SFO Museum has done to date. It will discuss the theory practice and gotchas of the work to date and solicit feedback, criticism and hopefully increased participation from the broader cultural heritage sector. The goal is to demonstrate that we have agency beyond a monthly-recurring fee to third-party vendors.

This session rapidly introduces 15 experimental visitor-facing GenAI prototypes we developed and tested at The Met over the course of six months. These sketches are the product of The Met’s inaugural “Technologist in Residence,” a position focused on quickly and iteratively exploring emerging tech with our visitors. The goal of these past six months was to explore the potential for AI in the on-site experience: what’s working, what’s not, and what questions does this work raise—within the organization, and with our visitors.

Our goal is to move beyond theory and provide a practical library of examples that other museums can use to inform their own AI experiments, and that show what is currently possible with GenAI. We’ll cover novel ideas, tracking nascent visitor AI backlash, small successes and outright failures.

The prototypes cover a wide range of use-cases across the museum experience, including physical navigation, tools for close-looking single artworks, collaborative games, and experiments connecting art to the outside world. For each prototype we will share our most important findings, including what visitors found useful, what they ignored, where the technology failed, and where great ideas are butting up with current technical limitations.

We will end our presentation by taking a step back and sharing our large-scale conclusions, open questions, and next steps towards a sustainable implementation of our findings.

Building on a history of metadata innovation, the Mead Art Museum at Amherst College has deepened its commitment to digital accessibility following the launch of a new internal and public-facing online collections database. This initiative centers on a strategic collaboration between the museum and the college’s Academic Technology Services (ATS). Utilizing an investigative workflow involving generative AI models, undergraduate students—under the joint supervision of museum and technology staff—produced descriptive narrations for art and material culture objects.

In their roles as coders, editors, reviewers, researchers, and narrators, undergraduate students refined AI-generated outputs, simultaneously developing critical AI literacy. Their application of "Responsible AI" was guided by a human-centered ethic, requiring rigorous fact-checking, vigilance against algorithmic bias, and the calibration of descriptive style to align with established accessibility guidelines. The preliminary results from this student cohort underscore the necessity of "Human-in-the-Loop" strategies. Furthermore, the project demonstrates that expert museum intervention remains essential to ensuring factual accuracy and maintaining social and cultural sensitivity.

This work-in-progress establishes a model for peer institutions where trust in museum metadata and the transparency of automation tools are integrated directly into the professional workflow. Beyond digital discovery and broadened access, these detailed descriptions serve as a vital institutional archive for inventory purposes and as a resilient analog resource. By providing printed or QR-coded visual descriptions, the museum ensures that objects on display remain accessible to low-vision visitors, bridging the gap between digital innovation and physical gallery experiences.

As museums and cultural institutions explore AI-driven discovery tools, a critical question emerges: how do we design generative experiences that enhance discovery while sustaining institutional trust over time? This session shares early exploratory work from the National Gallery of Art rethinking search through the lens of Generative UI (GenUI), an emerging interaction model where interfaces dynamically adapt, synthesize information, and guide users through more personalized discovery journeys rather than relying solely on static keyword-based search results.

Drawing from ongoing cross-collection search initiatives and AI-assisted prototyping work at the National Gallery of Art, this session will explore how generative search experiences may help visitors navigate complex cultural content, begin searching without knowing exact terminology, and engage with collections through more intuitive and exploratory pathways. At the same time, these systems introduce important questions around transparency, interpretive authority, bias, user expectations, and the long-term stewardship of institutional knowledge.

Through a short case study and examples of generative search concepts and prototypes, the session will examine how UX design and human-centered research can help museums experiment responsibly with emerging AI technologies while maintaining clarity, credibility, and public trust. Rather than presenting a finalized solution, this talk offers a framework for how cultural institutions can thoughtfully evaluate and prototype AI-mediated discovery experiences during a period of rapid technological change.

Robots, fever dreams, and artworks with escape fantasies: for more than ten years, the Harvard Art Museums have been asking what really happens when we trust AI to look at our art. What began as a practical effort to improve search and discovery by augmenting curatorial descriptions with machine‑generated synthetic metadata has grown into a long‑term experiment in co‑creating knowledge with machines.

Over that time, we’ve processed more than 500,000 images (depicting artworks, archival material, and exhibitions and galleries) and amassed over 120 million synthetic annotations to enrich our collections catalogue. Today, new images entering our systems are automatically queued for processing by a “panel” of commercial services: Amazon Nova and Rekognition, Clarifai, Imagga, Google Gemini and Vision, Microsoft Cognitive Services, OpenAI GPT, Anthropic Claude, Meta Llama, Mistral, Qwen, and others. Together, these models tag features, write descriptions, identify colors, read text, detect faces, and more. Their outputs are compared, combined, and surfaced through our public API (hvrd.art/api) and AI website (ai.harvardartmuseums.org) alongside human‑written cataloguing. This processing is not a temporary experiment, but part of how we work. It’s baked into our data pipeline and designed so that new models can be added over time, recognizing that describing collections is a forever project. Opinions, interpretations, and experiences of art are always in flux, for humans and machines alike.

Along the way, we’ve learned that the real questions are not just about accuracy. What happens when humans and machines look at art together? How much does “accuracy” matter for material that is inherently subjective? How can we embrace the inconsistencies, hallucinations, and disagreements between models (and between models and people) to broaden how collections are described and experienced?

This solo session will share concrete examples from over a decade of practice, including short collective looking exercises where attendees attempt to reconcile their own responses to artworks with those of AIs. We’ll explore how this work has changed our thinking about trust, authorship, and longevity in collections data, and how we are designing systems where AI is a long‑lived, transparent tool in the hands of people, rather than a faceless, monolithic black-box of implied authority.

Over the course of more than a year, a cross-functional team from the Getty including data engineers, catalogers, and frontend developers coordinated remotely with our counterparts at the Rijksmuseum in Amsterdam. The remit was simple: How do we surface the ways our collections connect? Given that our collections are both modeled in linked open data, specifically Linked Art, given that our technical stacks are aligned, and given that both institutions promote open collections often and publicly -- what could we actually do that practically demonstrates our shared commitment to open standards? After months of planning, the collaboration culminated with an in-person, hands-on prototyping session. The point was to explore, focusing on what was lightweight, likely ephemeral, and leveraged existing resources and expertise. 

The process ended up helping us shine a light on core institutional concerns: using shared data models in real-life; authority, branding, and UX issues; organizational differences across institutions; and just how collections ought to live outside our own museum contexts. This talk touches on what we can learn (and unlearn) when we go beyond talking about data models and start building a working app from scratch alongside an unfamiliar team.

Many museums are already doing AI engagement work, including exhibits, programs, community conversations. But what's the full range of what's possible, and how do you know where your institution fits? This session introduces a typology of 13 roles museums can play in AI public engagement, organized across four domains: building AI awareness and knowledge, facilitating public input into AI development, strengthening AI-related infrastructure, and exploring AI's social impact and meaning. Developed by the Association of Science and Technology Centers through a cross-sector workshop process, the framework offers a shared language for a field that is moving fast and often in parallel. Come map where your work already lives, and where you might want to go next.

What does it take to navigate last-minute resistance on the eve of a collections-wide portal launch after two years of planning and execution? How do you avoid the derailment of an already moving train?

In mid-2025, The Huntington launched a pan-collections portal that combines our three collecting divisions —the Library, the Art Museum, and the Botanical Gardens— into one cohesive discovery platform on our main website.

The objective was straightforward and in-line with our 5-year strategic plan: create a simple, navigable, and accessible online space for casual users to explore all our collections without having to navigate three separate formal research sites. Although the launch of this discovery portal took nearly two years of planning and execution, at the midnight hour, we experienced a near mutiny from our curatorial teams who were unaware of and expressly displeased with the need to consolidate cataloging and metadata practices to a cross-divisional level. They felt like they were losing control over the collections they're responsible for, and they didn’t like that. 

This is a case study of how the discovery portal team had to quell anxieties and problem-solve our way into proceeding with an imminent launch, despite objections.

We will discuss the development and execution process, where things went wrong, and the steps we took to address these last-minute concerns and build trust among our internal users, particularly our curators.

We will also cover what sustainability looks like after implementation: governance, clear decision rights, documentation, and a workable path to raise issues, so problems aren’t solved ad hoc—or by the loudest voice.  Attendees will leave with a fresh perspective on how disagreements, especially at the most critical moments, are opportunities for positive change and encouragement in team building and trust-building.

Museums are being asked to make decisions about AI and take on new roles and practices at a moment when both the technologies themselves and the social expectations surrounding them are evolving rapidly. This session shares the synopsis of the Museums and AI convening funded by the Institute of Museum and Library Services in spring 2026, which brought together museum professionals, technologists, educators, researchers, and institutional leaders to reflect on the current state of AI in the museum field, imagine possible futures, and identify what support museums need in order to engage with AI responsibly and effectively.

Drawing from facilitated discussions, scenario-building exercises, and thematic synthesis conducted after the convening, this session presents what museum professionals currently see as the most promising and most likely trajectories for AI adoption in museums, as well as concerns and ethical issues. Rather than framing AI as either an inevitable solution or an existential threat, the session examines the nuanced perspectives that emerged across the convening.

One theme that emerged was exploring AI use for internal workflow efficiency, particularly where these tools could help address museums’ chronic capacity limitations, in contrast to visitor-facing AI experiences, with concerns about the trust the public has in Museums, hallucinations and misinformation, intellectual property, transparency, and the potential erosion of human interpretation and expertise. The convening also revealed significant concerns about uneven institutional capacity across the field. Leaders raised the issue that AI adoption could widen existing inequities between large, well-resourced museums and smaller institutions lacking staffing, technical expertise, policy guidance, or experimentation capacity. 

Many other themes arose, including AI policies, ethical use, improvements to accessibility, environmental concerns, use of Open Access and other content as AI training sets, complexities in working with AI vendors, AI literacy in the public and in museum staff, rapidly changing legal implications,  leadership skills necessary for meeting the moment, and how funders can best understand and support museums in this moment. 

Finally, participants identified significant needs for shared field-wide support, including ethical frameworks, implementation guidance, professional development, peer-learning networks, and stronger forms of AI literacy grounded in museum contexts and values.

Rather than focusing on what AI is, specific tools, or individual implementations, this session offers attendees a high-level synopsis of how museums across the field are currently thinking about AI, unpacking these themes to document where major tensions and opportunities are emerging, where there was consensus, and when viewpoints differed, and how institutions can approach AI adoption in ways that align with mission, public trust, equity, and long-term institutional values.

How do you modernize critical exhibit systems without disrupting the visitor experience? This session explores how the 9/11 Memorial & Museum is upgrading the backend infrastructure that powers its digital exhibits. From replacing outdated technologies to introducing containerized systems and real-time monitoring, this work ensures reliability at scale while supporting millions of visitors each year. Learn how to approach modernization in a live museum environment, make the case for change, and implement upgrades that improve both operational stability and long-term sustainability.

When the 9/11 Memorial & Museum opened in 2014, its digital exhibit systems were built using technologies that were appropriate at the time but have since become outdated. Over the years, these systems have remained central to the visitor experience, supporting some of the most meaningful and interactive elements of the Museum. However, maintaining reliability and performance at scale has become increasingly challenging. This session focuses on how we are modernizing the backend infrastructure that powers three core interactive exhibits: the Memorial Exhibition interactive, the Signing Steel Kiosks and Projected Map, and the Last Column interactive. These experiences allow visitors to engage deeply with the stories of victims, leave personal reflections, and explore artifacts connected to first responders and recovery workers. The goal of this modernization effort is not just to replace outdated technologies, but to ensure long-term stability, scalability, and ease of management. I will walk through how we evaluated the existing systems, identified risks associated with legacy components, and prioritized upgrades while keeping the exhibits fully operational. A key part of this work involves moving to a containerized architecture using tools such as Docker Compose. This shift allows us to standardize deployments, improve system reliability, and reduce the complexity of maintaining multiple applications. In parallel, we are modernizing our content management capabilities, making them accessible so exhibit staff can more easily manage and update digital content without heavy technical dependency. Another important focus is observability. By integrating modern monitoring and logging tools, we now have real-time visibility into system performance and usage patterns. This not only helps us proactively address issues but also provides valuable insights into how visitors interact with these exhibits. Throughout the session, I will also discuss the practical side of this work—how to build a case for modernization within a museum setting, how to balance risk and continuity, and how to execute technical upgrades in a live, high-traffic environment.

The best exhibit technology disappears. A visitor reaches for a screen, a button, and a story unfolds. That invisibility requires, in practice, a set of architectural decisions that many museum platforms never make — decisions that determine not just who can experience an exhibit today, but whether the system holding it together will still hold up after exhibits rotate, content changes, audience needs shift, staff turns over, and the vendors you launched with are no longer the vendors you have.

At the Obama Presidential Center, we treated accessibility and longevity as architecture problems. The result is a centralized exhibit platform powering the OPC's digital experiences. It spans cloud-based content authoring, a MongoDB-backed exhibit API, on-premises Docker services, and a fleet of devices — touchscreen kiosks and dedicated accessibility UXP devices — all drawing from the same content and event model. Every device, whatever its form, is a client of the same system. The visitor at the touchscreen and the visitor at the UXP station are not having parallel experiences maintained by separate codebases. They are having the same experience, delivered differently. Accessibility decisions in museums are often mistaken for content decisions — alt text, audio descriptions, alternative formats. These matter, but they are downstream of something more fundamental: whether the system itself was designed to serve more than one kind of visitor.

This didn't emerge from the architecture. It is the architecture.

Building the suite of services taught us that the decisions with the deepest impact on accessibility and longevity are rarely the visible ones — and that getting them right early is what makes everything else possible. The unglamorous choices about how content is shared, how devices communicate, and how much the running exhibit depends on live infrastructure turned out to be the choices that had the most impact.

This session is a case study in those decisions — how we made them, what they cost, what they produced, and what we would do differently. The OPC had dedicated engineering resources that many institutions cannot count on. We don't want to paper over that. But the principles that guided us are not proprietary, and the questions they answer — who can access this, and will it last — are ones every institution is already living with, whatever their stack.

I hope to leave attendees with a clearer sense of what trustworthy exhibit infrastructure can look like, and a vocabulary for advocating for it in their own contexts.