Tag: algorithms

Growth & Engagement

Welcome back, friends and family! This week I also posted the following: Breaking Down the Misinformation & Disinformation Ecosystem – The challenge in identifying misinformation from disinformation rests in the purpose of intent of the sender. My Ratio of Signal to Noise – How might I best leverage these spaces, places, and texts to build…

The Coming War

The Coming War Digitally Lit #271 – 12/05/2020 Thank you for being here. You are valued. This week I worked on the following: Trust, But Verify – Users of the Internet become pawns in a flow of information that circulates endlessly in the ether causing a contagion that is nearly insurmountable. Shades of Gray -…

Digitally Literate #228

Digitally Literate #228 Under Observation Digitally Lit #228 – 1/11/2020 Hi all, welcome to issue #228 of Digitally Literate. If you haven’t already, please subscribe if you would like this to show up in your email inbox. If you’re reading on the website, feel free to leave a comment behind. You can also use Hypothesis…

Digitally Literate #222

A Broken World Digitally Lit #222 – 11/16/2019 Hi all, welcome to issue #222 of Digitally Literate, thanks for stopping by. Please subscribe if you would like this to show up in your email inbox. This week I posted the following: National Council of Teachers of English Defines Literacy in a Digital Age – Last…

The Messy Reality of Algorithmic Culture

danah boyd argues that we need to develop more sophisticated ways of thinking about technology before jumping to hype and fear. Data-driven and algorithmic systems increasingly underpin many decision-making systems, shaping where law enforcement are stationed and what news you are shown on social media. The design of these systems is inscribed with organizational and…

The Devastating Consequences of Being Poor in the Digital Age

Mary Madden discussing the privacy and security violations that occur in our increasingly digitized society. This is increasingly true for marginalized and vulnerable populations. The poor experience these two extremes — hypervisibility and invisibility — while often lacking the agency or resources to challenge unfair outcomes. Madden draws on work that focused on privacy perceptions…

The Age of Cultured Machines

The Age of Cultured Machines (SAPIENS)

Two robots traverse the desert floor. Explosions from a decades-old conflict have left a pockmarked and unstable territory, though many more improvised bombs lie concealed in its vast reaches. Sunlight splays off the beaten edges of Optimus, the smaller robot. Its motors whir as its claw grasps an u…

From Sapiens. This imaginary scene shows the power of learning from others. Anthropologists and zoologists call this “social learning”: picking up new information by observing or interacting with others and the things others produce. Social learning is rife among humans and across the wider animal kingdom. As we discussed in our previous post, learning socially…

How ‘Googling it’ can send conservatives down secret rabbit holes of alternative facts

How ‘Googling it’ can send conservatives down secret rabbit holes of alternative facts (washingtonpost.com)

We saw some of this happening in earlier research on online reading comprehension. Specifically, I had concerns about how algorithms might impact, shape, or modify what we’re looking for. “Googling it” has become the news equivalent of “do your own research.” But neither Google, nor search terms, are purely neutral. “Even in the face of research…

Algorithmic Accountability: A Primer

Algorithmic Accountability: A Primer (Data & Society)

Algorithmic Accountability examines the process of assigning responsibility for harm when algorithmic decision-making results in discriminatory and inequitable outcomes. The primer–originally prepared for the Progressive Congressional Caucus’ Tech Algorithm Briefing–explores the trade-offs debate

Big decisions about people’s lives are increasingly made by software systems and algorithms. This primer explores issues of algorithmic accountability, or the process of assigning responsibility for harm when algorithmic decision-making results in discriminatory and inequitable outcomes. There are few consumer or civil rights protections that limit the types of data used to build data…