On the concept of Continuous Accessibility (CI/CD/CA), machine learning, and iatrogenics.

Edition No. 22: A few brewed thoughts, two curated links, and one good read.

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Few Brewed Thoughts

→ Do you truly need more information, or do you need to improve the way you capitalize on the information you already have?

Capitalizing is taking advantage of what’s there. We often scramble to gather more data to convince ourselves that our assumption is the right one (confirmation bias). Don’t start adding more though before you’ve determined how to benefit from and feed what you already have. Otherwise, you risk losing it. Raise the quality of the questions.

→ You have to learn to pace yourself in various races.

The physique and skill of a 100m runner is not the same of a 400m runner, but the key is to take the coaching you (hopefully) receive, and figure out how to adjust the race you run through practice over distance and time.

One runner takes on corners in a different way which requires you to learn a different skill, and both of those runners has to sprint the last 50m, yet no matter the various races you’ll come across, you must learn the different ways to pace yourself leading up to that. It’s a different race, but remember, you’re still an athlete with a lot of skill to be applied. Pace yourself.

Two Links

Checks and balances: Machine learning and zero-knowledge proofs

“Current models today are made by ingesting an enormous amount of publicly available text and data, but only a small number of people right now control and own those models. More specifically, the question isn’t “will AI be tremendously valuable,” the question is “how do we build these systems in such a way that anyone interacting with them will be able to reap its economic benefits and, if they so desire, ensure that their data is used in a way that honors their right to privacy.”

The same electricity that powers the lightbulb so too powers the electric chair. It’s long known that any new technological advancement can be used in the most innovative and creative ways—like helping a paralyzed man walk again via his thoughts thanks to scientific progress and LLMs. However, we can’t ignore the nefarious ways it will be manipulated. Artificial Intelligence and Machine Learning models aren’t immune to this. But in building the technology and software for tomorrow, we’re obligated to ask ourselves: what are the downsides? Who is impacted? That doesn’t mean we put a complete halt to the technology, but we must be cognizant of the checks and balances needed to mitigate the downside risk—be it legislation in government or an ethics board.

Iatrogenics: Why Intervention Often Leads to Worse Outcomes

“Despite our best intentions, thinking forward increases the odds that you’ll cause harm (iatrogenics). Thinking backward, call it subtractive avoidance or inversion, is less likely to cause harm. [...] Inverting the problem won’t always solve it, but it will help you avoid trouble. You can think of it as the avoiding stupidity filter. It’s not sexy but it’s a very easy way to improve.”

One Good Read

Raising the bar for digital accessibility: on the concept of Continuous Accessibility, how it’s transformative for digital accessibility, and why it’s at the center of Stark’s roadmap.

The next evolution of software design and development is CI/CD/CA, where continuous accessibility joins the mix of processes that are part of the everyday workflow.

“Today’s entire software landscape is driven by a “continuous” mindset. Teams build for CI/CD— continuous integration/continuous deployment—because that ensures an uninterrupted stream of product updates. On a parallel note, continuous monitoring ensures that around-the-clock protections are in place against security vulnerabilities and threats. In the same vein, we’re building an accessibility engine to power continuous accessibility. We want companies to ensure that accessibility checks are embedded into every step of the development process, from crafting designs to writing code, from shipping products to creating social graphics.

As always, thanks for reading! And if you have any questions, go ahead and AMA by replying to this email or pinging me on Twitter. If I don’t have the answer, we’ll deep dive together.

I appreciate you. Until next time…

Cat.