Shared Links (weekly) Jan. 18, 2026
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Why technologists need to get involved in public policy? – Bruce Schneier
Bruce makes some interesting points in this presentation, it’s certainly something to think about. First, watch: I’ll be honest, I’ve been on the side of leaving technology alone for the most part, but his point about the legal industry, and how public policy law is a huge area of focus, and how even law schools…
Why Training Matters for Diversity
Wouldn’t it be a better choice to locate candidates with some of the skills you’re going to need in a position and know that you have an environment that will help them grow and learn to become exactly what you need to be? Wouldn’t that practice become a way to attract really smart people who want to grow and learn by coming to work for you? Doesn’t that sound like a better option than simply leaving your open jobs unfilled and lamenting the fact that no one wants to work anymore? Unfortunately, there are too many organizations that simply won’t consider this. They aren’t interested in growing the people who work for them, they only want to hire people who can come in with no effort on the organization’s part and do the work starting on day one.
I think they are short-sighted.
Linked – Why Your FOIA Request Might Not Get Text Messages
This is mostly because it’s too difficult and/or expensive to retain SMS messages, but I have another takeaway. “In other words, only 22 percent of FOIA requestors got everything they asked for. 22 percent!” The demand for the Federal government to move this percentage higher is going to result in a lot more scrutiny of…
Worth Reading – AI Is Killing The Billable Hour (And It’s About Time)
For lawyers and other professionals, billing hours is indeed a dumb approach. It hasn’t made sense in years. If AI finally pushes that out of our way, we’ll owe it thanks for that alone. I don’t think AI is good enough to do work on its own, though, so the question then becomes, what are we billing for? Where’s the work? Do you have solid baselines for how much value AI brings versus how much a human is having to contribute to make up for times when the AI falls short, and who decides that?
Linked – Have the Right Expectations Regarding Artificial Intelligence
Sharlyn chalks this up to AI still learning, but I don’t believe that’s correct. I don’t think Generative AI tools can come up with anything new. That’s not the way it works. Large language models are developed by ingesting and analyzing tons of existing data. Based on that data, they then mathematically conjure up the most likely response to your prompt. How could it come with a genuinely original icebreaker?
