&gt; This isn&#x27;t high risk though. It&#x27;s low risk.<p>I meant &quot;high risk&quot; in the sense that the return has a high variance, with all of it being concentrated in a thin sliver of the probability; apologies if I&#x27;ve misused a technical term.<p>&gt; The problem here is that you could make this same argument about almost anything, a la Pascal&#x27;s Wager.<p>I&#x27;d call it a consequence of expected return being a widely-applicable calculation, rather than a &quot;problem&quot; per se. Even if we knew the expected returns, we&#x27;d still need a decision procedure to perform the allocation.<p>My point is that it&#x27;s uncontroversial to avoid putting all funding into the most promising project (e.g. other Physics research doesn&#x27;t wait until we&#x27;re &quot;finished&quot; with the LHC), so there&#x27;s certainly scope for allocating a small budget to more &quot;fringe&quot; research like the EmDrive. I&#x27;m not in charge of research budgets, but as a simplified argument we might imagine allocating funding on an exponential scale, based on expected return and risk: the most promising projects compete for a chunk of half the funds, the &quot;second tier&quot; projects for a quarter, and so on. Projects with lower impact are lower tier, projects with lower probability of success are lower tier. We stop once we&#x27;ve rounded-up an allocation to the smallest unit of funding, hence avoiding Pascal&#x27;s Wager.<p>Also note that there are only a finite number of options to choose from, because there are only a finite number of submitted research proposals.