Things that we can do to start getting on top of things again:

• invest into observability & traceability: it's important to understand how
  a system behaved and why. Especially with more and more AI systems around,
  there are no longer humans who made the rules.

• write less code: feature creep is the biggest enemy of robust systems. The
  question always needs to be: does the customer really need this?
• more respect for humans: loose the idea that humans can be simulated by
  algorithms. They are far too complex.

Human individuality needs to be front and center when developing technology. The
ACM Code of Ethics is a good starting point to start re-centering tech around
the human: https://www.acm.org/code-of-ethics

Exploratory testing is a key skill to invest - across all professions.
@alex_schl has a great talk on this topic,
already: https://www.youtube.com/watch?v=ksqhuXSuzFA It's about the skill to
think outside of the box and apply this to systems in order to uncover blind
spots.

Great summary in this slide: the testing principles used by
@alex_schl and
@huibschoots.

Great talk, @alex_schl. Thank you!

More great links from the talk:

https://reallifemag.com/fair-warning/
http://www.huibschoots.nl/wordpress/?p=2763
https://www.heavybit.com/library/podcasts/o11ycast/ep-16-observability-and-test-engineers-with-abby-bangser-of-moo/
https://www.honeycomb.io/wp-content/uploads/2019/08/From-Unstructured-Logs-to-Observability-Honeycomb.pdf
https://www.honeycomb.io/developing-a-culture-of-observability/
https://www.buzzfeednews.com/article/mikemonteiro/we-built-a-broken-internet-now-we-need-to-burn-it
https://www.newyorker.com/tech/annals-of-technology/the-hidden-costs-of-automated-thinking