Grim news heralded in a report published this week by the Video Game History Foundation, which claims that 87% of video games released before 2010 are no longer commercially available. This equates to a lacuna of tens of thousands of works, many of which represent key moments in the medium's evolution. It's an excruciating loss of source material for the people who worked on these games, as well as for historians and archivists, for gem-hunters and for any younger player who might wish to enjoy interactive works created in different socio-political circumstances, against different technological constraints and fashions or within different market conditions. The void is not unique to video games – there are books that are no longer published even in digital form, some films can only be watched on defunct formats, others disappear from streaming services mere months after release – but the scale of the video game void is unmatched in other media. According to the report, less than 5% of games from the Commodore 64 are still available today.

This article examines the impact of Artificial Intelligence on the archival heritage digitization processes, specifically regarding the manuscripts' automatic transcription, their correction, and normalization. It highlights how digitality has compelled scholars to redefine Archive and History field and has facilitated the accessibility of analogue sources through digitization and integration into big data. The study focuses on two AI systems, namely Transkribus and ChatGPT, which enable efficient analysis and transcription of digitized sources. The article presents a test of ChatGPT, which was utilized to normalize the text of 366 letters stored in the Correspondence section of the Biscari Archive (Catania). Although the AI exhibited some limitations that resulted in inaccuracies, the corrected texts met expectations. Overall, the article concludes that digitization and AI can significantly enhance archival and historical research by allowing the analysis of vast amounts of data and the application of computational linguistic tools.

In a grainy video shot in the early 1980s on Carnegie Mellon University's campus, Ivan Sutherland rides on top of the Trojan Cockroach, a six-legged machine considered the first controlled by a computer and capable of carrying a person. Sutherland puts the machine through its paces, slowly walking forward, backward and sideways and turning 180 degrees in the video. At one point, he attempts to balance the massive machine on only two legs. "We believe that a mastery of balance will be important to future walking machines," Sutherland narrates over the footage. That Trojan Cockroach video, complete with Sutherland's prophetic comments on the importance of balance to the future of legged robots, is part of a new interactive, virtual exhibit from University Libraries and the School of Computer Science at CMU that explores the beginnings of and contributions to the field of robotics.

As an archivist, I'm excited about what disruptive innovations like non-fungible tokens (NFTs) and artificial intelligence may mean for archives. These developments pose existential threats to our field, and by extension, to the survival of human history and culture. I give old films away for free. It started in 1999 when I was seduced by the promise, excitement, and just-felt-rightness of the gift economy. Not 30 seconds after we first met, Internet Archive founder Brewster Kahle asked me, "Want to put your film archives online for free?"

From wars to weddings, Europe's history is stored in billions of archival pages across the continent. While many archives try to make their documents public, finding information in them remains a low-tech affair. Simple page scans do not offer the metadata such as dates, names, locations that often interest researchers. Copying this information for later use is also time-consuming. These issues are well-known in Amsterdam, which is trying to disclose its entire archives.

—Rebecca Bayeck and Azure Stewart “Artificial Intelligence and Archives” was the inaugural webinar of the series on Emerging Technologies, Big Data & Archives, organized by CLIR postdocs Rebecca Y. Bayeck of the Schomburg Center for Research in Black Culture and Azure Stewart of New York University. With the emergence of new technologies and big data, the processing and preservation of data has changed and will continue to change. As in other domains (e.g., health, video games), artificial intelligence (AI) is increasingly reshaping the way we process, interact with, and think about archives. Consequently, in the age of big data, archives are not just “a collection of historical records relating to a place, organization, or family” (Cambridge Dictionary Online). Today, archives also include all types of digital data—including social media data—and algorithms. Archivists are therefore called on to preserve and process data as they are being created, which requires understanding AI languages, processes, and practices for the creation and protection of data/records now for the future. In this webinar, our speaker Dr. Anthea Seles, from the International Council on Archives (ICA), discussed AI in archival spaces: its uses, application, and the role archivists should play to become critical voices in AI discussions. Two hours were not enough to address all the questions raised by the 280 attendees. As a follow up to the webinar, we have thematically organized and addressed the unanswered questions and present them here. Artificial Intelligence in Archives How much has AI penetrated archives in the developing world? I would say [this has been] limited, if at all. I think the main issue is that these technologies are being applied in the assessment of development initiatives like Sustainable Development Goals (SDGs). Increasingly there are many projects focusing on artificial intelligence and human rights, for example the University of Essex Human Rights, Big Data and Technology Project, and it is becoming a concern for organisations like Amnesty International. Who already has the best AI for archives today, according to ICA regulation, that we can adopt? There is no commercial provider that works specifically on archival questions. I think you can use off-the-shelf eDiscovery software, but you need to have a basic understanding of what the technology is doing in order to measure your precision and recall.  Artificial Intelligence Tools Will governments and big corporations use artificial intelligence as a tool to centralize information in future? Potentially. I think there is some thinking about this coming out of the records management community, but I still believe it is about balancing the strengths of the tool with the continuing need for human intervention. The question is, when will the human be needed? And what can the tool be trusted to do with minimum supervision? How do we ensure a continuous feedback loop to identify records of long-term value as information creation changes?  What tools were you using for the file analysis and visualization in this presentation? The screen shots are only example photos, they are not from any of the tools we used. We looked at several eDiscovery tools with different algorithms (e.g., Latent Semantic Indexing, Latent Dirichlet Allocation). These are bog standard machine learning applications that have been around for a while, and we chose to go down that road to see what we could get in off-the-shelf commercial software packages. So, is there a way to write a script to avoid metadata corruption and alteration? There are tools now you can use that will preserve the integrity of the metadata when you move material from one system or file to another. I think for historical metadata alteration/corruption it is a question of how we explain this to users and how this might affect different access methods like visualisation.  Will the International Council on Archives provide training on artificial intelligence and machine learning? Not yet, but I’m open to suggestions. [We are] currently speaking with different stakeholders and maybe we can hold a hackathon at the Abu Dhabi Congress.  Access to Archives Will the course Managing Digital Archives be accessible online? The managing digital archives course is organized by the ICA and will be accessible online in fall 2020. Please check the ICA website or social media channels (Twitter and Facebook) for more information. What are some of the practices in the UK National Archives and government on managing structured data as records? How does the UK identify, capture, manage, and apply retention and disposition to data (both transactional applications and analytical ones)? There are no published policies on identification of datasets that I can see and would suggest you contact either the record copying or the UK government web archive records unit to see if anything more substantive has been developed. What is your suggestion for keeping physical records for posterity and authentication? Records should always be maintained in the format in which they are created. The belief in scanning paper records and destroying them in order to save space and save on storage costs is a false economy. The level at which you should be scanning that material and the amount of metadata that should be captured to maintain it over time is very high. Also, you need to take into account computer storage costs, and whether you can afford the costs of digital preservation software, which all begins to add up. One must also take into account the active management of these authentic digital surrogates by digital preservation specialists. Furthermore, if you have a paper management problem and you don’t take that into account when you move into the digital environment you are then transferring an analog integrity issue into a digital integrity/authenticity issue. Digital will not solve integrity issues; in my opinion it will magnify them. Artificial Intelligence and Society In Brazil, we are concerned with the problem of the spread and political use of misinformation (fake news). How can archivists with algorithm training provide reliable research insights to fight against this historical problem? At this point, I couldn’t honestly provide you with an answer but Read More

A growing body of work shows that many problems in fairness, accountability, transparency, and ethics in machine learning systems are rooted in decisions surrounding the data collection and annotation process. In spite of its fundamental nature however, data collection remains an overlooked part of the machine learning (ML) pipeline. In this paper, we argue that a new specialization should be formed within ML that is focused on methodologies for data collection and annotation: efforts that require institutional frameworks and procedures. Specifically for sociocultural data, parallels can be drawn from archives and libraries. Archives are the longest standing communal effort to gather human information and archive scholars have already developed the language and procedures to address and discuss many challenges pertaining to data collection such as consent, power, inclusivity, transparency, and ethics & privacy. We discuss these five key approaches in document collection practices in archives that can inform data collection in sociocultural ML. By showing data collection practices from another field, we encourage ML research to be more cognizant and systematic in data collection and draw from interdisciplinary expertise.

VANCOUVER, British Columbia--(BUSINESS WIRE)--Lucidea, provider of ArchivEra, CuadraSTAR SKCA and Eloquent Archives, enjoyed a very successful experience at this year's Society of American Archivists (SAA) annual conference. Traffic to their booth was the highest ever, with attendees eager to see how easily their archival collections management solutions enable researchers and the public to connect with the historic materials archivists work hard to preserve. Lucidea's archives specialists demonstrated the powerful and versatile capabilities of ArchivEra, CuadraSTAR SKCA, and Eloquent Archives that make them a valued technology partner in the archives community. Importantly, SAA attendees were the first to see Lucidea's exciting new AI prototype for archives. With Artificial Intelligence (AI) integration now available in ArchivEra, Lucidea's clients will enjoy powerful automatic categorization functionality.

Lucidea, provider of ArchivEra, CuadraSTAR SKCA and Eloquent Archives, enjoyed a very successful experience at this year's Society of American Archivists (SAA) annual conference. Traffic to their booth was the highest ever, with attendees eager to see how easily their archival collections management solutions enable researchers and the public to connect with the historic materials archivists work hard to preserve. Lucidea's archives specialists demonstrated the powerful and versatile capabilities of ArchivEra, CuadraSTAR SKCA, and Eloquent Archives that make them a valued technology partner in the archives community. Importantly, SAA attendees were the first to see Lucidea's exciting new AI prototype for archives. With Artificial Intelligence (AI) integration now available in ArchivEra, Lucidea's clients will enjoy powerful automatic categorization functionality.

Lucidea, provider of ArchivEra, CuadraSTAR SKCA and Eloquent Archives, will participate in the Archives & Records Association (ARA) annual conference on 28th and 30th August in Leeds. Visit Lucidea at Stand #5 in the Queens Hotel to see how easily their archival collections management solutions enable researchers and the public to connect with the historic materials archivists work hard to preserve. Lucidea's archives specialists will demonstrate the powerful and versatile capabilities of ArchivEra, CuadraSTAR SKCA, and Eloquent Archives that make them a valued technology partner in the archives community. ARA attendees will be first in the UK to see Lucidea's exciting new AI prototype for archives. With Artificial Intelligence (AI) integration now available in ArchivEra, Lucidea's clients will enjoy powerful automatic categorization functionality.