Complexity of computing the average distance of a graph
Computing ad(G) in $O(n^{2-\delta})$ time for constant $\delta&gt;0$ even in graphs with $\tilde{O}(n)$ edges and $n$ vertices would imply that the Strong Exponential Time Hypothesis (SETH) is false. (SETH was defined by Impagliazzo, Paturi and Zane'01 and implies that CNF-SAT on $n$ variables does not have $O(2^{(1-\varepsilon)n})$ time algorithms.)

To prove this, note that we recently proved in (Fast approximation algorithms for the diameter and radius of sparse graphs, Liam Roditty, V. Vassilevska Williams. STOC'13.) that if one can distinguish between graphs of diameter 2 and 3 in subquadratic time, then SETH is false. 
The proof goes via a reduction from CNF-SAT.
The same reduction can be used to show that computing ad(G) in subquadratic time shows that SETH is false, as the average distance in the graphs in the reduction would be $2-M/{N\choose 2}$ (where $N$ and $M$ are the number of nodes and edges in the reduction instance) if the CNF-SAT instance is not satisfiable, and more than that if there is a satisfying assignment.