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==== Overview ==== | ==== Overview ==== | ||
In our final discussion session together, we'll be discussing ways to stay engaged in privacy work in libraries and beyond. Alison will share about LFP next steps, including some highlights of work being done by other members, and ways to continue being involved with the LFP community. We'll also discuss people and organizations to follow in the privacy field, as well as places to get further information and resources, from websites to conferences. Finally, we'll hear from everyone in this Crash Course about what they've learned and what they're thinking about for next steps. | In our final discussion session together, we'll be discussing ways to stay engaged in privacy work in libraries and beyond. Alison will share about LFP next steps, including some highlights of work being done by other members, and ways to continue being involved with the LFP community. We'll also discuss people and organizations to follow in the privacy field, as well as places to get further information and resources, from websites to conferences. Finally, we'll hear from everyone in this Crash Course about what they've learned and what they're thinking about for next steps. | ||
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| + | email stuff more | ||
| + | tor browser | ||
| + | organize by tier different | ||
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| + | issues with your work sending you test emails to see if you will fall for phishing attempts...like emails about covid vaccines!! | ||
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| + | Relatedly, a list of popular apps that collect the most user data, so like Instagram. | ||
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| + | Much is made of the coming artificially intelligent future, where automation takes away menial labor and self-driving electric cars get us off the internal combustion engine. But that fantasy ignores the reality of the AI infrastructures currently being built, infrastructures that exacerbate existing social problems and create whole new concerns. Artificial intelligence is built through enormous datasets, which are often created from the wealth of information collected about us without our consent. Processing all of this data is incredibly resource-intensive. Furthermore, lots of AI is used for even greater privacy-violating purposes, like facial recognition and predictive policing. This week, we'll talk about AI in depth and efforts to oppose its worst excesses. We'll also talk about health and privacy, the connections between digital health and artificial intelligence, and patient privacy rights. | ||
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| + | ==== Readings ==== | ||
| + | * Anatomy of an AI report and visualization of the data, labor, and ecological impacts of one Amazon Echo device from AI Now Institute: https://anatomyof.ai/ | ||
| + | * The far-right helped create the world's most powerful facial recognition technology: https://www.huffpost.com/entry/clearview-ai-facial-recognition-alt-right_n_5e7d028bc5b6cb08a92a5c48 | ||
| + | * Palantir provides Covid-19 tracking software to CDC and NHS, pitches European health agencies: https://techcrunch.com/2020/04/01/palantir-coronavirus-cdc-nhs-gotham-foundry/ | ||
| + | * Defund facial recognition: https://www.theatlantic.com/technology/archive/2020/07/defund-facial-recognition/613771/ | ||
| + | * (Optional long read) Bad predictions: how civil rights violations impact police data, predictive policing systems, and justice https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3333423 | ||
| + | * (Video) Dr. Adrian Gropper on patient privacy issues and rights: https://vimeo.com/520441452 | ||
| + | * Notes and social media graphics from LFP's Health Privacy and Literacy in a Pandemic World series https://healthandprivacy.com/notes/ | ||
