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Amelia Acker, "Archiving Machines: From Punch Cards to Platforms" (MIT Press, 2025)
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- [00:01]
Amelia Acker
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- [01:01]
Amelia Acker
Welcome to the New Books Network.
- [01:05]
Adam Kreisberg
Hello, everyone, and welcome back to the New Books Network. This is New Books in Library Science. My name is Adam Kreisberg, and I'm an associate professor at the Simmons University School of Library and Information Science. And I'm really happy today to be joined by Amelia Acker, who is an associate professor in the School of Communication and Information at Rutgers, the State University of New Jersey. And she's joining me today to talk about her book, Archiving Machines From Punch Cards to Platforms, which was published in late 2025, November, I believe, by MIT Press. Hi, Amelia.
- [01:44]
Amelia Acker
Hi, Adam. How's it going?
- [01:46]
Adam Kreisberg
It's going great. Thanks for being here. Really excited about this, really enjoyed the book. And before we get into our discussion, I should say full disclosure, we go back to I think we met in 2011 when we were both graduate students, and it's really awesome to see you publishing this book these years later. It's a really interesting and fascinating project and can't wait to hear more about it.
- [02:16]
Amelia Acker
Yeah, me too. I'm excited to talk with you about it.
- [02:19]
Adam Kreisberg
All right, great. So let's get right into it. And as a means of introduction for our listeners who may not be as familiar with your work, I'd love to hear a of lot a little bit about your background and sort of what led you to this project. What kind of questions have you been asking in your research in the past that helped you scope out this book project?
- [02:46]
Amelia Acker
Great. Yeah. Well, I'm an information scientist who uses archival perspectives to study how we preserve and represent data over time. And I used to be a processing archivist, so I train archivists and librarians now at Rutgers. And I've always really been interested in cell phones and personal computers and their history and how they're changing not only the data that we're creating, but our own record keeping practices as a society in this moment. So that's a little bit about my background. Before the pandemic in 2018, 20, 19, 2020, I was doing a project on software emulation. So I got an opportunity to go to the Media Archaeology Lab at the University of Colorado Boulder and the Living Computers History Museum in Seattle to look at how different people were preserving and providing access to software and hardware. And that's when I sort of came up with this idea of thinking about how did machines start to archive things, and when did we expect machines to do some of this automated process or automated data management for us? So that's sort of the origins of the history of the project. But I guess probably the biggest thing that started me on that journey was about 10 years ago, my students started using archiving as a verb. So when we start our classes, we usually say, why are you here? What do you want to be? And I just noticed students started saying, I'm really interested in archiving the music scene that I'm a part of. Or it's really important to me that we start archiving the movement for black lives. Or I am an archiver. And I got really interested in, like, when did archivists themselves begin to use that word? And what are the many meanings of archiving not only in the history of computing, but also in the history of our field?
- [04:42]
Adam Kreisberg
Interesting. Yeah. You know, I think. Well, it's. It's nice to hear that your students helped kind of inspire part of, part of the book project. I'm sure they would appreciate hearing that as well. So. Yeah. So the book itself is impressive in its scope and sweep. It really covers much of the 20th century, and in fact, the epilogue is much more contemporary even than that. But it sort of covers the period from the earliest computers through some of the personal computing revolutions of the later part of the 20th century, with a series of interesting vignettes which you add your own perspective to, again, as a sort of information science scholar, which I think is a much appreciated and really important perspective to add to these historical narratives. So I'd like to start off roughly following the book with talking about the National Data center that's one of the first big examples that you talk about. And the National Data center is a complex project. It's been discussed by other scholars, but you again, you sort of place it within this larger data management evolution and process alongside the history of computing. So I'd love to hear specifically you talk about what the story reveals, about the tensions that you set up in this first example that animate the rest of the book and that sort of echo across the later dilemmas and tensions around data management.
- [06:30]
Amelia Acker
So, yeah, so the National Data center is a really fun case study. And as you say, it's been written about by a lot of different historians from sort of American political or statistical perspectives. But I'm really interested in talking about it in terms of the story of the transition from punch cards to data tape. So that's sort of how the case study begins. So in the early 1960s, computers started migrating from paper punch cards to magnetic data tape in a lot of different professional areas, not just in the military. So government agencies and institutions like research labs and scientific repositories began to use minicomputers and magnetic tape to gather and collect data resources. And at the same time, a number of different professional groups of social and behavioral scientists, economists, and then what at that time was called data bank managers. But what we might think of as research data managers today started lobbying the federal government for access to public data. And these statistical researchers were really advocating for the government to take a lead, not only on providing access, but centralizing the government data that was already being collected at the state and federal level. And so a couple of different groups led to a presidential commission under the Johnson administration. And remember, at the time, the Great Society programs were also coming into effect. So if we had more data about voting, about literacy, about military service, it would help us create and leverage a better, more equitable society. So that was sort of the perspective for boosters or people who are really interested in creating the National Data Center. At the same time, Americans were very distrustful of the government. And as we were transitioning from punch card to magnetic tape, more institutions were collecting more information about Americans in ways that had never happened and had never been consolidated together. So there was a lot of pushback against what it meant to have more information being not only collected, but circulated by the government. So there were two or three congressional hearings in the summer of 1966 and 67, and they began with, what are the stakes of having a national Data center? But they ended with what does it mean to aggregate and network population level scales of Data and the federal Data Center. The proposals eventually failed. Many of the experts that testified in the hearings basically said we hadn't really thought about ensuring privacy through access because we trust in the government and the way that they collect information from citizens. Now many of the alarmists or the critics were concerned about the computer men that would have access to these powerful machines and what would be at stake if you could create new resources by aggregating data. And so this gets back to that migration or that externalization factor. Magnetic tape was not only mobile, but a lot easier to copy and aggregate. And so this is an example of American public debate really thinking about what are the stakes of aggregating data from citizens and what does it mean to appropriately provide access and protect that data at scale?
- [10:20]
Adam Kreisberg
Quickly, there's something that you mentioned towards the end of this case study which I also found really fascinating that the failure of the National Data center, given the act, you know, given the challenges or the warnings and risks that you do, that you mention in some ways paved the way for the privatization of large scale data collection that we see today. And this is just, it's a really effective foreshadowing for the end of the book.
- [10:48]
Amelia Acker
Yeah, yeah, yeah, totally. So the congressional hearings are cited as a motivating force for things like the 1974 Privacy act and a couple of other computer matching acts that prevent the federal government from aggregating or collecting citizens data over long periods of time. And what's important to remember about this is while we have legislation and policy that guards the federal government from collecting and aggregating our data in certain kinds of ways, they don't really have mechanisms for preventing private firms for collecting and aggregating population level scales of data. So from the 1960s onward, lots of different private firms, management companies, insurance companies, medical companies and so on, began to quietly collect Americans data and continue to today.
- [11:47]
Adam Kreisberg
Yeah, really, really interesting stuff. And I think we'll get back to some of those questions as we move through, through the book and through the rest of your narrative. I wanted to also maybe ask you a really kind of a deceptively basic question which you, which you unpack in the next part of the book where you, where you again sort of trace, trace the evolution of computing technology alongside practices and norms around data management. So the question is what is a file? And how does the definition of this term changing reflect changes in people's expectations and understanding of how computers work over the 20th century?
- [12:35]
Amelia Acker
Great. Yeah. So files in a really basic sense, I think for information scientists and for practitioners who really study them are just thinking of them as abstractions. So the way that I usually describe files when I'm teaching is that it's basically a way of bundling stuff. And the best part about the idea of a file in digital context is that we can use these bundles to build more bundles. So we can have things like file directories or a meaningful structure for lots of different kinds of ordinal or different types of flavors of data that are really important for not only how we provide access to computing services and storage, but also how we retrieve things and describe them. So files have been like this animating abstraction in the field for about 200 years, depending on who you ask, and they really look different today. And so one of the heuristics that runs through the book is this idea of grammars of action. It comes from this scholar named Phil Agri. But grammars of action are basically these ways in which we approach different information systems and how we make sense of them as users. And grammars of action as they relate to files really change depending on which sort of data formats we're thinking about or talking about. So they really, really transform from punch cards to sequential data tape. And then eventually when we move to more mobile devices like PDAs or personal computers, the idea of the file is still there, but it meaningfully has a very strong technical difference when it comes to organizing or naming data. The biggest difference between files in the 80s and 90s and files today is that most of our computing environments assume wirelessness or connecting to the Internet. So more and more files have been disappearing in our operating systems and our software and our hardware. So people now, today, I guess contemporary computing culture is sort of organized around the app. And what the app does is it actually disappears files, they're still there, but they're more automated and hidden from the user. And I'll tell you, like, as an instructor who teaches digital preservation, all of the ways that we think about preserving born digital things is through this idea of file and file directories. And when you're working with young people who come from a computing culture of apps where files have been disappeared, it's a really hard a conceptual framework to, to build an approach. And so this is another reason I think is, I don't want to say this history of data management and digital formats is so important to practitioners like archivists or memory workers, because this disappearance of the file, an abstraction that has really organized most information systems for about two centuries. When we disappear it, or when it becomes automated, it really does Change not just the technical stakes for how we organize and access information, but, but also sort of the ontological or the political stakes of what does it mean to be able to find information once we store it or bundle it.
- [16:05]
Adam Kreisberg
Yeah, you know, it's interesting. A question I ask my students when teaching these sorts of digital preservation courses as well is about their personal information management style. Are they the type of, you know, asking them, are you the type of people who use your file directory to organize things into folders and subfolders and keep your work and school files separated? Or are you, do you lean on like Spotlight Search for Macs to find, to find documents and files that you're working on and most people lie somewhere in the middle. But I think a lot of students really do use that Spotlight Search, which like, as you're suggesting is sort of is kind of this, it's this tool to use the capacity of full text searching in modern operating systems to eliminate or greatly reduce the need for file management in the way that the 1960s and 70s computing professionals originally envisioned it. And yet if you go on Google Drive right now, the icons for folders are still. They look like they should be placed into a filing cabinet.
- [17:20]
Amelia Acker
I know, I know. Well, I think it's only a matter of time before they start disappearing. But yeah, they're still there. I think the Spotlight Search example is a really good point of how things have really changed in terms of how we access things. Again, one of the things that's really different about contemporary personal information management access points is it often pushes you towards the most recent document or item and also the most well traveled or most popular item. So Google Search for docs is going to send you to the documents that you're most collaborating and most updating, not the oldest, not the most rare, not the smallest files, which in these earlier forms of sorting and managing file directories is something that we would maybe give more consideration or different consideration and in ways that, you know, not necessarily lost but like in the grammars of action are maybe hidden or backgrounded increasingly in automated software environments.
- [18:20]
Adam Kreisberg
Yeah, that's, that's, yeah, interesting stuff. And as we both continue teaching, we'll see how student, what students, you know, make of this. Because one thing about, you know, archival work is that these computing environments of old are the very things that the, that the digital preservation professionals of today and tomorrow will need to preserve one way or another. All right, I wanted to kind of continue to walk through the book and actually I think the next big example that you just rep that you just hinted at, actually a little bit, a little while ago with the discussion of the assumption of wireless networking as a way of managing folders and files on people's computers today were some of the really interesting discussions that you got into about PD, PDAs, Palm Pilots and the like. And I was wondering if you could sort of talk about Palm Pilots and these and PDAs, because I. I'm of the generation where I remember my father having a Palm Pilot and messing with it and learning that Palm script with the stylus. Very poor. Graffiti. Graffiti. That's right. It was called Graffiti. That's right. And I wonder if you could sort of maybe situate that along this trajectory because again, it struck me as a really fascinating and overlooked technology or overlooked hardware format as we sort of imagine the progression of computers from mainframe computers to smartphones. So, yeah, what did the Palm Pilot predict about how we would think about files and manage our own information in today's computing environment?
- [20:12]
Amelia Acker
Yeah, I love that chapter on PDAs and the Casio Zoomer. I kind of see it as a hinge in the book that brings us from the past to where we are today, closer to the present. So in that chapter I'm really thinking about these early proto apps that were on personal digital assistants. For listeners who don't know what that is, it's like a smaller computer before the Internet. So early PDAs were in this kind of interesting consumer electronics era where people were beginning to have lots and lots of desktop computers at work, but more and more PCs at home. And PDAs started in the 90s, and they were primarily targeted to knowledge workers who were on the go, busy people that needed to go back and forth, but probably had computers in multiple places. And Jeff Hawkins, the founder of Palm, had this vision for personal portable data, and it was later sort of confirmed in some research that they did with early Palm Pilot users was that people wanted to carry their data from place to place. And PDAs largely failed in the 90s. But the people that designed them and really thought through them imagined a world where it wouldn't just be white collar professional workers or business business guys going to work, but it would be like high school students, college students, nurses, delivery workers. So much in the ways that we use phones today for a lot of our work, they were imagining this with PDAs in the book. I argue that this is actually a high watermark for users having control over their own personal information because these devices required us to actually manage our data and think about what does it mean to move it from one place to another, what does it mean to update our data or to carry it around with us on the go, if you will. So one of the through lines to the book is this idea that most archival machines are distancing from us, from our data. But a condition of that distancing, moving that data around in networks, is that we also increase our closeness to these machines. We increase the cadence of interactivity. Put another way, it's like the more data we create, the more we use these devices. And so the PDA is just a really great, I don't know, scene, I guess, for thinking about what would happen once we got our computers online with smartphones about a decade later. And so the PDA sort of presages this idea, this amplified world that we live in and that we should be constantly, not only creating data, but we should have access to data as part of connecting to the Internet or wireless networks.
- [23:19]
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- [23:46]
Amelia Acker
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- [23:48]
Adam Kreisberg
And also for those who may not be familiar with what the interface for for these PDAs looked like, I encourage you to go back and, and find some screenshots. And I and there are some in the book actually I and I gather that you took some of those photos yourself at places like the Computer History Museum. But yeah, if you look at a PalmPilot home screen, it looks like an iPhone screen, right? There are these rows of apps, Calendar notes, solitaire. Right.
- [24:20]
Amelia Acker
Almost every native app from those early PDAs are the same ones that come factory set on your phones today. And some really fun facts that I discovered like Intuit, QuickBooks and PayPal had their earliest apps on these early Palm machines in the 90s. And so you can see a lot of these third party developers or third party firms really thinking about what does it mean to meet the consumer or the user where they are and how can we get them to create more data or transport more data across networks with software like this.
- [25:00]
Adam Kreisberg
And of Course, Palm, as an innovator in this space, tried their hand at making a smartphone of their own, actually, which, which, which, interestingly enough, and you know, kind of reconsidering this story, it's surprising that it didn't actually grab hold because they had in some ways really mastered the software. But the Palm Palm phone didn't catch on, was not, it was not an iPhone killer.
- [25:25]
Amelia Acker
They just didn't have a good, they just didn't have an App Store, iTunes, I guess.
- [25:29]
Adam Kreisberg
Right. And actually, maybe that's, maybe that is actually really what it is. And it's interesting again that you're, you're tracing the origin of some of the most ubiquitous, you know, pieces of software that people use today, PayPal or, or intuit QuickBooks to these early Palm devices. They just couldn't necessarily make the switch into more networked platforms.
- [25:54]
Amelia Acker
Yeah, yeah, yeah, yeah.
- [25:56]
Adam Kreisberg
All right. Well, we're, we're really getting into the heart of the book at this point. And I would argue, you know, the sort of, the final, the largest, the final big case that you unpack and get into is the NSA cell phone data repository and its construction, its management maintenance and its associated scandal. So I, I wonder if you could sort of explain this. And again, I think the really interesting angle here is how you are talking really about metadata in this conversation. And as an information science scholar, I'm always thinking about metadata. And so I really appreciated that as well, because similar to the National Data center story, this is a story that has been covered in a lot of other venues and through other disciplines. But what you're talking about is not really the political implications of this, although of course that's part of the story, but really the sort of the, the, the power of metadata and how it has these political ramifications. So maybe if you could talk about that and break it down for readers who maybe would be interested in getting all the way to the end of the book.
- [27:20]
Amelia Acker
Okay, cool. Yeah. All right. So that this chapter is about making data with cell phones and cell phone towers. And another, another kind of conceptual thread in my work and throughout the book is this idea of born network records that increasingly the data that we're creating are records that are born in networks and are intended to be transmitted across them. So one of the things that is important about the scene here is that. Let's see, I wrote my dissertation about the history of the text message, and during that dissertation writing, the Snowden Leaks happened. So some people May recall in 2013, it was revealed that the NSA was collecting telephony metadata from every single American, not just cell phone records of interest, but every single person using a cell phone in the United States. All of their records are being hoovered up by the NSA. And as a result of the Snowden leaks, the USA Freedom act was passed in 2015, and it was a way for intelligence agencies to get signals intelligence from telephone companies without violating people's privacy. So that's sort of the background here, is that the USA Freedom act allows the NSA and other surveillance outputs to get access to telephony metadata in a meaningful and sensibly private way. In 2018, I noticed this kind of quiet. I think it was an article in the Washington Post that the NSA was deleting or destroying call data record archives. So giant big data archives were being destroyed. And at the time, the way it was reported was they were getting rid of these big data archives because they weren't useful and they were too expensive to run. And I just was obsessed with this. Why would we get rid of such a big data archive if it was so valuable and so important? And we have all this regulation and policy to ensure that we're able to collect them. So the case study sort of follows a couple of different privacy and civil liberties reports where they report on the government's use as part of transparency efforts. And what we find is that this archive of call data records wasn't useful as signal intelligence. And so this gets to your question about metadata. Call detail records, or CDRs, are this very fun type of document for us to think about, to fight about, because depending on your vantage point or the type of stakeholder you are, it can be data, it can be metadata, it can be meaningful information, or it can expire really, really fast. So CDRs are billing statements for telephone companies, but they're also really important for cell phone users. They're basically the networking record that makes the cellular connection possible. For signals intelligence, they can also tell us about who we're talking to and why. So the CER can be both data and metadata at the same time, but the more and more you collect, the less and less meaningful it can be. And so I talk about this big data empiricism that happened in the 2010s, where we were able to collect more and more volume and variety of data, but not necessarily make meaningful, actionable information or intelligence about it. I'm trying to think of, like, want to, like, keep going, but I'm not sure if I. If I've gone too, too far afield. Did I get your question?
- [31:25]
Adam Kreisberg
No. You. You Certainly did. The other analogy or sort of metaphor that you draw out in this chapter is this, and it's sort of what you were just talking about is the haystack analogy, where, where maybe that's one of the reasons why ultimately this was not useful for the NSA or for the, for the, you know, federal government's security apparatus in security agencies in the way that they thought. And it's, it is, it sort of is because of this, this haystack analogy and that this data turned into. It turned into a haystack with, with difficult to find needles, if you allow me to extend them at four.
- [32:05]
Amelia Acker
Well, I mean, I think that that was kind of the promise of the early big data era, was that if we just had enough haystacks, we wouldn't need to worry about the needle. We'd have everything. And I think that this example really shows that that haystack way of knowing is not always helpful, and it may take up more time and resources than necessary. There was some evidence that one of the reasons why they had so much noisy data or not useful data was because it was around that time when everyone started getting robocalls on their cell phones. So even persons of interest and terrorists get spammed just like everyone else. And that was a noisy amount of data that was unnecessary. CDRs that were filling up this big data archive or this big data architecture in a way that wasn't helpful or meaningful. It created more obstacles to finding the needle, if you will.
- [33:01]
Adam Kreisberg
Yeah, yeah. I mean, it's a really, again, a really interesting take on a story that I probably haven't thought enough about, really, when it comes right down to it. All right, well, as the book continues, you end with a really interesting epilogue, and I'd like also to give you an opportunity to reflect on that a bit here as we move towards the end of our conversation and maybe ask you a little bit about what you think the next frontier for archiving machines is. And probably a question that you have gotten a lot when discussing this book is what effect LLMs and AI systems might be having on the issued intentions that you raised throughout this story.
- [33:49]
Amelia Acker
Yeah, so I think we talked about this earlier in the conversation, but there are basically two conceptual heuristics that I'm trying to draw through in each of the chapters of the book. The first is this idea of grammars of action that condition us or habituate us to particular types of data practices and bring us closer to our machines. And also this idea of distancing techniques where archiving machines are sort of always already engaged in, in terms of taking over data management and also bringing us closer for interactivity. The grammars of action really help us unpack new types of routines that have been carried over through different generations of information technology. And so things like saving a file on a disk or saving a file in the cloud means something really different than saving a file into ChatGPT, for example. But grammars of action help us sort of trace this state genealogy in an important way. So one of the things that I'm trying to end with the epilogue, is to get us to think about what does it mean to constantly have our data collected and being accessed by platforms or big tech firms? And I'll give you an example of, I think, the stakes of archiving machines for AI today. I was listening to this interview with a product manager from Claude Code this morning, and he was talking about how Claude Code is an agent that's supposed to help you make more decisions. And he said, we built the agent so that it can be configured across different surfaces, not just your primary computing device, but your cell phone, different types of apps, and different types of platforms. And the idea here is that eventually you'll be able to get the agent to configure your own configurations for the agent. And this is kind of like that big data empiricism and distancing at the same time. So this is sort of a archiving machine in action that's happening to us right now. And distancing that I'm trying to talk about in the book is sort of this epistemological act of faith that we put into these machines and their automated systems. And I think as we start adopting more and more agents or more and more LLM applications, we really need to consider, what does this mean for access in the future? Probably one of the most animating and important questions that we can ask as archivists or memory workers. And, you know, like Tracy Kidder said, that software is something that users don't give up. You know, they don't discard it once it works. So once we start adopting these agents, and now they're appearing in all of our information tools, you know, our word processor, our browser, our text messaging, WhatsApp, once we adopt them, it's hard to get rid of them. And they will continue to distance us from our data and also increase our interactivity and in computing environments. So I really think that means that we should consider them really closely. And I think it also gives us an opportunity to think about some of the narrative work that we need to do about having control over the data that we're gifting to these tech companies. And I think that's probably like reflecting on the failure of the national data center. That was a moment in American life where publicly and in Congress we made moves to develop policies to think about how data that is being aggregated can be safely and securely assembled. And it might be a way for us to be inspired for thinking about this particular moment in terms of policy and our politics, you know, towards working with these new agents who are archiving machines, I guess.
- [38:04]
Adam Kreisberg
Yeah. The new, the new generation of archiving machines, if you will. Yeah. I'm always drawn to these kind of fundamentally archival questions which you were just hinting at around access. Right. Like what would it take or how could you imagine access working for these systems or for files produced by these systems in 50 or 100 years, or for a user who hasn't been born yet. Right. These are the, these are the fundamentally archival questions that, that, that some of the other stakeholders involved in these kinds of conversations don't always ask. And which I, which I, which I feel in which again, to return to the students, which I really try to emphasize to my students, is the is, is one of the really unique perspectives that we, that we try to give in, in this particular moment when teaching students about digital preservation and archiving for digital records.
- [39:06]
Amelia Acker
So I talked about at the beginning, one of the motivations was how the verb gets used by our students. And I've also done some work on how it gets used by practitioners. And one of the projects that I was trying to do in that etymological journey that sort of started the book was to try to understand when did archiving become something that archivists started adopting from a borrow word, if you will, from that history of computing. And one of the things that I learned is that in mid century definitions of archiving, it's about taking data offline, not keeping it constantly active or having it accessible all the time, but safely and securing it and taking it offline and putting it to rest. And even in those early practitioner discussions in the 60s and 70s about tape library and scientific data tape, there was this strong commitment and concern about how to keep data secure and safe for the future, but not constantly be accessible or appended, if you will. And so one of the things that I really want to encourage with the, I don't know, with the offering, at least for practitioners, is for us to think about how do we take data and actually meaningfully take it offline or put it to rest in sort of these earlier definitions or perspectives of the term when we're thinking about collections of digital data and providing access and preserving them.
- [40:41]
Adam Kreisberg
Yeah. What, what does preservation really actually look like for this stuff? That's, that is a good question and certainly fundamentally practitioner focused. One.
- [40:51]
Amelia Acker
Yeah. Yeah.
- [40:53]
Adam Kreisberg
Well, well, as you move towards the end of this conversation, I guess two questions really. One, is there anything else that we haven't covered that you wanted to sort of mention from the book? And, and number two, even though I know a little bit about the answer to this, if you're, if you're willing to share a little bit about what's next for you and what projects you're currently cooking up, I think the listeners would love to hear.
- [41:18]
Amelia Acker
Yeah, well, I think one of my favorite things about the book is that it surfaces a few different early data bank managers and some cool stories about graduate students and sort of different stories about actors that have been shaping data formats in ways that like, we don't always get to highlight in, I don't know, regular histories of computing. So I think that that was pretty fun. There are a couple of cool data bank managers and data archivists that I got to read and engage with. And that was really neat, I think. I love the stuff about PDAs and cell phones. And if you're interested in thinking more about what is a file, what is a file on a phone, I'd really point you to that chapter in particular. And then I guess I'd also share that the press has generously made the book open access. You can download different parts of it and each chapter standalone if that's interesting to you. So I encourage you to check that out. It's at mitpress, I think dot com.
- [42:26]
Adam Kreisberg
Yes, and we'll certainly leave. We'll include a link to the book, including a link to the open access version in the show notes for everyone. So, yeah, thanks for mentioning that as well.
- [42:37]
Amelia Acker
Yeah. In terms of future work, I'm starting to think about how should we be preserving software in the near future? Like, what does software look like for what we're doing right now, especially in the cloud? Our shared drives, our cloud driven browser experiences, things like Slack, things like cloud code. How should we be thinking about documenting those things? Those have some really interesting and wacky stakes for not only foreign networked records, but what archival access will really look like in the near future. And so I've been studying and thinking up on that and I think that'll probably be my next project. And as ever, I continue to think about social media social media data archives and how we are also, like, preserving things that are coming from and created in private platforms.
- [43:36]
Adam Kreisberg
Yeah, you know, well, thanks for that, and I think that's something for everyone to look forward to for some future work from you. I One final note about my students and our students is I still get a lot of traction with our students out of talking about the Library of Congress Twitter archive project. Speaking of speaking of social media archives and what that project, again, actually, to sort of borrow a frame from the book, what it presages about our the current state of the field when it comes to records on platforms and private data collection and the interaction between public and private entities with regards to these large, large data collections.
- [44:21]
Amelia Acker
Yeah, I think it's like, such an exciting space because it's clear that libraries and archives have really been thinking about access partnerships for so long, but we are often like the last people at the table for some of these access tools. And so one of the things that's like a challenge, but also an opportunity for us, I think, is to just start thinking about how can we lead part of these new conversations in the context of access for private and public spaces in the near future?
- [44:58]
Adam Kreisberg
Yeah, great. Well, that's plenty for us as researchers and practitioners to keep in mind. Well, Amelia, I really want to thank you again for being here and for sharing this work with us on the show, as well as to the broader reading public. Once again, this has been the New Books Network, New Books in Library Science, and I've been speaking with Amelia Acker about her book, Archiving Machines, out now from MIT Press. Thanks, everyone.