  We study the volatility of the output of a Boolean function when the input
bits undergo a natural dynamics. For $n = 1,2,\ldots$, let $f_n:\{0,1\}^{m_n}
\ra \{0,1\}$ be a Boolean function and
$X^{(n)}(t)=(X_1(t),\ldots,X_{m_n}(t))_{t \in [0,\infty)}$ be a vector of
i.i.d.\ stationary continuous time Markov chains on $\{0,1\}$ that jump from
$0$ to $1$ with rate $p_n \in [0,1]$ and from $1$ to $0$ with rate $q_n=1-p_n$.
Our object of study will be $C_n$ which is the number of state changes of
$f_n(X^{(n)}(t))$ as a function of $t$ during $[0,1]$. We say that the family
$\{f_n\}_{n\ge 1}$ is volatile if $C_n \ra \iy$ in distribution as $n\to\infty$
and say that $\{f_n\}_{n\ge 1}$ is tame if $\{C_n\}_{n\ge 1}$ is tight. We
study these concepts in and of themselves as well as investigate their
relationship with the recent notions of noise sensitivity and noise stability.
In addition, we study the question of lameness which means that $\Pro(C_n
=0)\ra 1$ as $n\to\infty$. Finally, we investigate these properties for a
number of standard Boolean functions such as the majority function, iterated
3-majority, the AND/OR function on the binary tree and percolation on certain
trees at various levels of the parameter $p_n$.
