The problem goes this way. There are $20$ watches, $2$ of which are broken. And there is an expert who can say if the watch is broken. But his verdict is only correct with probability $0.8$ - in both cases, if the watch is broken and if it is not. So, then I choose one watch, show it to the expert and he says: it's broken. I choose then another watch of these $20$. What is the probability that this second watch is broken? Thanks in advance.
PS. I dont really understand how this information can help, but let it be. My math background: PhD, but it is 20 years ago, so I'm not an active mathematician anymore. The source of the problem: a student who i know. What I tried: naturally, Bayes theorem. But I still cannot solve it.
PPS. I found the solution. It goes without Bayes but with the law of total probability. Its rather technical.

I did use Bayes' Theorem for this (along with the Law of Total Probability.)
Let $B_i$ be the event that the $i^{\text{th}}$ watch is Broken, and let $R_i$ be the event that the expert Reports that the $i^{\text{th}}$ watch is broken. We want to find $$ P(B_2 \vert R_1) = \frac{P(R_1\vert B_2)P(B_2)}{P(R_1)} $$ $$ = \frac{P(R_1\vert B_2)P(B_2)}{P(R_1\vert B_2)P(B_2) + {P(R_1\vert B_2^c)P(B_2^c)}}. $$ Certainly $$ P(B_2) = \left(\frac{2}{20}\right) $$ and $$ P(B_2^c) = \left(\frac{18}{20}\right). $$ It remains to calculate $P(R_1\vert B_2)$ and $P(R_1\vert B_2^c)$.
Part I: To find $P(R_1\vert B_2)$, let us simply assume that $B_2$ is true. So for now, we assume $B_2$, and calculate $P(R_1)$ under this assumption. Since the second watch is broken, we know that of the $19$ other watches, exactly $1$ is broken. Now $$ P(R_1) = P(R_1 \vert B_1) P(B_1) + P(R_1\vert B_1^c) P(B_1^c) $$ $$ = (0.8) \left(\frac{1}{19}\right) + (0.2) \left(\frac{18}{19}\right) $$ $$ = \frac{4.4}{19}. $$
But this was calculated under the condition that $B_2$ is true. Thus we have really shown that $$ P(R_1\vert B_2) = \frac{4.4}{19}. $$
Part II: To calculate $P(R_1\vert B_2^c)$, we simply assume that $B_2$ is false. Under this assumption, $$ P(R_1) = P(R_1 \vert B_1) P(B_1) + P(R_1\vert B_1^c) P(B_1^c) $$ $$ = (0.8) \left(\frac{2}{19}\right) + (0.2) \left(\frac{17}{19}\right) $$ $$ = \frac{5}{19}. $$ Because this was calculated under the assumption that $B_2$ is false, we have really shown that $$ P(R_1\vert B_2^c) = \frac{5}{19}. $$ Collecting our results together, we find that $$ P(B_2\vert R_1) = \frac{\frac{8.8}{380}}{\frac{8.8}{380} + \frac{90}{380}} = \frac{22}{247}. $$