How do you reduce null hypotheses Type 2 errors?

Type II errors are the case of false negatives. In hypothesis testing, we begin with a speculative hypothesis. A type 2 error is created when the test fails to reject the null hypothesis, when the alternative hypothesis is, in reality, true. The null hypothesis can be thought of as the status quo, and the alternative hypothesis is what our experiment is telling us. You can reduce type 2 errors by increasing alpha. However, by increasing alpha, type 1 errors increase, that is to fail to accept the null hypothesis, when the alternative is, in reality, false. Is there any way to reduce both errors? If you increase your sample size (of course with good data), for the same alpha, both will decrease. The understanding of this is very important. It happens with mad cow disease. The tests were very good at identifying that a healthy cow was, in fact,a healthy cow. In thousands of tests, they never had an error. So type 1 errors never occurred, but they had so few cases of sick cows, that it was hard to know if type 2 errors, a cow was sick, but the test showed healthy, ever occurred.