Mathematically speaking, we have two random variables X1 and X2 that assume values 1, 2, and 3 with the given probabilities. The first eye is better seeing than the second one if X1 ≤ X2 (or X1 < X2 for strictly better seeing). So we need to find P(X1 ≤ X2). The event X1 ≤ X2 can be broken into several disjoint events:

X1 = 1, X2 = 1

X1 = 1, X2 = 2

X1 = 1, X2 = 3

X1 = 2, X2 = 2

X1 = 2, X2 = 3

X1 = 3, X2 = 3

The probability of the union of the first three events is the same as P(X1 = 1). For the rest, assuming that vision acuity in different eyes is independent, we can multiply probabilities: P(X1 = m, X2 = n) = P(X1 = m)P(X2 = n). Therefore, the probability that the first eye sees at least as well as the second one is

0.1 + 0.2 * 0.2 + 0.2 * 0.8 + 0.7 * 0.8 = 0.86.