$-z_\frac{\alpha}{2}$ and $z_\frac{\alpha}{2}$ in Confidence Intervals I was watching a Youtube video about Confidence Intervals and came across a slide that threw me:

I get that the blue region is $1-\alpha$ (often 0.95 in practice) while the bits to the edge are each $\frac{\alpha}{2}$ (often 0.025 in practice).
However, I don't understand the tick marks down the bottom. Why can't they instead be respectively $z_{\frac{\alpha}{2}}$ and $z_{1-\frac{\alpha}{2}}$, so that in the case of a 95% Confidence Interval they'd come out as $z_{0.025}$ and $z_{0.975}$. Those values come out to -1.96 and 1.96, as per the following R code
qnorm(0.025)
qnorm(0.975)

I must be missing something obvious because this video has many comments but nobody has previously tried to 'correct' it. It'd be much appreciated if someone could explain how the tick-marks in the video are in fact correct, and why my interpretation is wrong or not as accurate.
There is a related question, in which the poster says

I got used to the convention that $z_{\frac{\alpha}{2}}$ is such a
value that $P(Z>z_\frac{\alpha}{2}) = \frac{\alpha}{2}$. It also
follows that $-z_{\frac{\alpha}{2}} = z_{1-\frac{\alpha}{2}}$

However, I still don't understand the logic of the convention, or why it should be preferred to just writing the tick marks as $z_{\frac{\alpha}{2}}$ and $z_{1-\frac{\alpha}{2}}$.

People sometimes find it easier to work with positive numbers and use explicit +/- signs
Firstly, as you may already be aware, the use of $-z_{\alpha/2}$ and $z_{\alpha/2}$ is allowed here because of the symmetry of the standard normal distribution.  The symmetry of this distribution around zero allows us to conclude that the respective critical points with upper and lower tail areas of $\alpha/2$ are the negation of one another.
As to why this convention has evolved (as opposed to just using the standard normal quantile function as you propose), it has probably come about because people find it easier to work with fundamental quantities that are positive numbers and then impose a negative sign on them when they want to turn them negative.  By framing the analysis in terms of the critical point $z_{\alpha/2}$ (defines as having upper tail area $\alpha/2$) you always get a positive critical point value, so when you put a minus-sign in front of it you get a negative value.  The aesthetic advantage of this framing is that the sign of the critical points in the analysis is obvious from the notation, rather than having to be inferred from knowledge of when the quantiles are positive or negative.  For experienced mathematicians and statisticians this is unlikely to matter, but people with less familiarity with the problem might find it helpful.
