Nana

That discovery led me to entirely new archives that hadn’t been on my radar before.

And at the Eisenhower library, as I researched religious nationalism in the 1950s, I found a document that once again subverted the expectations I originally had (and that AI would still have)

Instead, I launched myself into the archives and soon found that religious conservatives in the 1960s were strongly influenced by the politics of religious nationalism (In God We Trust, etc) of the 1950s — even though the literature (which AI would’ve used) told me that was meaningless.

Nope!

If I’d asked AI to guide me, it would’ve mapped out the book I envisioned in my head because, like me, it would’ve drawn its conclusions just from what we already knew. No surprises.

When I planned my second book, I originally planned to do a grassroots study of the communities that formed the Religious Right.

I thought it’d be focused in the 1960s and 1970s, revolving around a counterrevolution on social issues.

Absolutely right.

AI might be able to summarize (poorly) what we currently know, but a major goal of historical research is to find the hidden surprises out there.

Let me illustrate …

To be seen and supported through life events is a student’s greatest wish. Thank you Steve. Academics need to do better.

An @abeba.bsky.social tweet turned into a protest banner artwork at BCU MA graduate show. Brilliant!

We are thrilled to finally introduce our lab members aial.ie/people/

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we at @aial.ie, are investigating amplification/censorship on X/twitter in EU. what are major EU:
-politicians & regulators
-journalists
-influencers & public intellectuals, with high visibility/influence on X, across both left & right political ideologies

we're interested in existing datasets too

Hi Hellina! I’ll like to suggest ‘We Need New Names’ by Bulawayo, Dream Count from Chimamanda Adichie and ‘The Girl with the Louding Voice’ by Abi Dare

Computer-vision research powers surveillance technology - Nature An analysis of research papers and citing patents indicates the extensive ties between computer-vision research and surveillance.

New paper hot off the press www.nature.com/articles/s41...

We analysed over 40,000 computer vision papers from CVPR (the longest standing CV conf) & associated patents tracing pathways from research to application. We found that 90% of papers & 86% of downstream patents power surveillance

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