No, the last articles and discussions were quite clear that this accident wouldn't have happened with a real driver. The road conditions were good, the visibility was good. A driver would have seen the woman crossing the road well enough and slow down.
However, I don't think it's reasonable at all to expect someone to remain attentive while looking at a self-driving car. This is the same problem train drivers face, which has been mitigated with all sorts of methods, least of which a dead-man switch. Some countries let their train drivers mention every signal they come across to themselves, with Japanese train drivers even pointing at signs to ensure they're paying attention.
This was a vehicle that had been modified to reduce certain safety features (because Uber couldn't get them to work properly) with someone at the wheel expected to be 100% focused on the road while giving them nothing to do at the same time. You can only go through so many hours of sitting in a card doing nothing before you go crazy.
From a revenge-seeking perspective it's easy to blame the one person who could've stopped the car for her obvious disregard for safety (streaming video on the job), and I suppose a criminal justice case might be in order. However, I think Uber should be mainly responsible for the loss of life because their flawed design not only made the car less secure but also completely disregarded the human psychology when they designed how their human safeguard driver should do their job. Even human-operated cars will beep and yell at you if you don't pay attention while you're driving in cruise control, if such safety features were omitted in the self-driving design then clearly the driver was set up to take the fall when something bad would happen.
I strongly believe Uber only put that woman in there because local law wouldn't let them test their car without a human at the wheel, not because they wanted to ensure their car didn't kill anyone.
I think pointing out things in the environment is a great idea for safety drivers in this kind of setting. It helps keep them engaged, possibly helps the system notice when they're distracted, and possibly provides additional useful training data.