Posted by: bluesyemre | August 8, 2019

#ComputerScience could learn a lot from #LibraryandInformationScience


Computer science curriculums have long emphasized the power of data, encouraging its harvesting and hoarding, pioneering new ways of mining and manipulating users through it, reinforcing it as the path to riches in the modern economy and proselytizing the idea of data being able to solve all of society’s ills. In contrast, library and information science curriculums have historically emphasized privacy, civil liberties and community impact, blending discussion of public data management with private data minimization. Tomorrow’s future technology leaders could learn much from their library-minded colleagues.

As a young computer science student at what was then the #4-ranked computer science program in the nation (today #5), my coursework was filled with all manner of practice and theory on how to acquire, manage and mine the world’s largest datasets.

The focus was on capability, of what “could” be done with data, rather than what “should” be done with data. The idea that a technical achievement should be avoided because it might harm society was never even whispered. The idea that data should be minimized to protect privacy was not even a concept. Secure systems design emphasized how to safeguard data from unauthorized access, but never the concept of how to safeguard the users whose data that was from harm.

Never once was the concept of an Institutional Review Board or the concept of assessing the societal harm of research ever presented, even while security and architectural review boards were a topic of regular discussion.

In contrast, as a doctoral graduate student at the university’s library and information science (LIS) program just a few blocks away, it was like entering an entirely new world.

The concept of societal harm was brought to the forefront the very first semester, emphasizing the idea of avoiding promising research that could have cause significant harm to vulnerable communities, the idea of IRB review of research and the notion that even publicly downloadable data like social media datasets still required a full consideration of risks and a complete ethical review.

Algorithms were no longer piles of code, they were a compilation of human assumptions, priorities, worldviews and biases that guided the creation of that particular algorithm rather than one very similar, even if the actual code itself was produced through machine learning. Indeed, these are concepts still absent from computer science today, where models are described as “unbiased” replacements for biased programmers.

Data security was no longer technology-centric “cybersecurity” but rather user-centric “privacy” in which safeguarding data meant safeguarding a user from harm, not merely locking down a server.

Even beyond the concepts of privacy and data, there is a vast world LIS programs can teach computer scientists about how to think about their users.

Front and center in the LIS world is the study of how individuals seek out, consume and act upon information. That artists don’t just patronize art libraries, but rather voraciously consume all available material about a subject they are depicting, seeking to understand it not just in its physical dimension required for depiction but its deeper meaning and motivation and societal impact. While little surprise to art majors, such insights into how different disciplines seek out and utilize information offers powerful insights into how we can design better information platforms.

A deeper understanding of information behavior can help platforms design systems that are more resistant to the spread of digital falsehoods and avoid common pitfalls.

A few classes in “use and users of information” and a primer in reference librarian training could have helped social media platforms avoid the common pitfalls of the backfire effect in their “fake news” efforts and perhaps even avoided the idea of mob rule virality-based algorithmic prioritization in the first place.

An understanding of the global evolution of how societies have generated, managed, consumed and utilized information throughout history and especially the ways in which societies across the world have differed in their approaches, can offer powerful guidance in the shaping of today’s informational systems. In place of the Western-centric view of information management, the interplay between information and society in other parts of the world offers myriad lessons for how to combat the spread of digital falsehoods, foreign influence and violence-inducing purposeful manipulation today. The ways past societies addressed information scarcity and the evolution of the gatekeeping model also has much to teach platforms struggling with how to moderate their informational free-for-alls. The difference between evidence and interpretation, expertise and experience, information and knowledge all have much to contribute.

Cataloging theory could help today’s AI researchers contemplate how to build their taxonomical classifiers, while abstracters and reference librarians could impart their immense wisdom and experience on tomorrow’s digital assistants, smart speakers and Q&A systems.

Yet LIS curriculums are about far more than managing archives of physical artifacts and electronic subscriptions. Community engagement has long been a major emphasis, with disciplines like “community informatics” emphasizing how information and communications technologies can empower and strengthen communities. In a digital world in which “worth” is typically defined by “advertiser interest” there is much the major internet platforms could learn from a broader thinking of how their tools empower or repress community and the meaningful changes they could make to better support marginalized and vulnerable communities.

Indeed, much of the harm wrought by social platforms on the vulnerable communities of the world, their contributions to ethnic violence, genocide, hate crimes and other horrors could have been considerably mitigated had the companies from the very beginning approached their designs from community-centric mindsets rather than building a system in their own image and answering each harm with today’s glib “oops our mistake but no-one could have foreseen this” responses. Community informatics researchers study these very issues and many of today’s high-profile social media failures are eerily reminiscent of the topics covered in the classes I myself took years ago.

Sadly, however, as Library and Information Science schools have undergone a wave of rebrandings over the past decade into “iSchools,” this emphasis on data minimization and privacy, use and users of information, community informatics, civil liberties and the human dimension of informational creation and consumption has been steadily eroded in favor of the same harvesting, hoarding, mining and manipulation that were once the exclusive domain of computer science programs.

As LIS schools boost their hiring of computer science graduates, this transition is accelerating. At some schools, LIS scholarship traditions have been relegated to specialty tracks, with core programs looking almost indistinguishable from “light” computer science curriculums.

In what would have been unthinkable during my own tenure, LIS job candidates lured from computer science are increasingly dismissing privacy, societal harm, ethical review and community engagement in favor of data-driven understanding at all costs. One particularly striking LIS job talk I attended featured a computer scientist who proudly advertised how they had bulk harvested vast swaths of major social media sites and subscription services and was redistributing them freely to researchers all across the world in direct violation of legal agreements, excitedly detailed their work on unmasking vulnerable communities, touted their years of work advancing governmental foreign influence campaigns, dismissed the utility and necessity of IRB ethical review and presented a vision for working closely with governments and Silicon Valley companies to leverage LIS approaches to building the ultimate surveillance machine. Rather than being booed from the room, this individual was enthusiastically embraced and was not only hired, but became a research director.

Sadly, as Library and Information Science schools pivot into iSchools and hire waves of computer scientists, the scholarly traditions of the community-centric human focus of LIS are giving way to the data-driven technical focus of computer science.

In the end, there is much computer scientists can learn from the library and information science community. If they hurry, they might just be able to learn some of it before it all gives way to the data-driven wave crashing across academia.

Kalev Leetaru Contributor
Based in Washington, DC, I founded my first internet startup the year after the Mosaic web browser debuted, while still in eighth grade, and have spent the last 20 years working to reimagine how we use data to understand the world around us at scales and in ways never before imagined. One of Foreign Policy Magazine’s Top 100 Global Thinkers of 2013 and a 2015-2016 Google Developer Expert for Google Cloud Platform, I am a Senior Fellow at the George Washington University Center for Cyber & Homeland Security. From 2013-2014 I was the Yahoo! Fellow in Residence of International Values, Communications Technology & the Global Internet at Georgetown University’s Edmund A. Walsh School of Foreign Service, where I was also adjunct faculty. From 2014-2015 I was a Council Member of the World Economic Forum’s Global Agenda Council on the Future of Government. My work has appeared in the presses of over 100 nations.

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