Having concluded that a national RBID is inadvisable at this time, a natural follow-up question is what this conclusion means for the state-level RBIDs currently in operation in Maryland and New York and as may be implemented by other states. Although the core arguments that can be made against a national RBID can be applied to a state RBID, we conclude that the smaller-scale state databases are critically important proving grounds for improvements in the matching and scoring algorithms used in ballistic imaging. Indeed, they provide an ideal setting for the continuing empirical evaluation of the underlying tenets of firearms identification in general. The state databases can be a critical, emerging testbed for research in ballistic imaging and firearms identification.

Early in ATF’s work with the IBIS platform, Masson (1997:42) observed that as ballistic image databases grew in size, the IBIS rankings tended to produce suggested linkages that might look promising on-screen—and might also be tricky to evaluate using direct microscopy:

As the database grew within a particular caliber, 9mm for instance, there were a number of known non-matched testfires from different firearms that were coming up near the top of the candidate list. When retrieving these known non-matches on the comparison screen, there were numerous two dimensional similarities. When using a comparison microscope, these similarities are still present and it is difficult to eliminate comparisons even though we know they are from different firearms.

Far from undermining the utility of the system, Masson (1997:43) argued that this finding presented a critical learning opportunity. “In the past, best examples of known nonmatched agreement were collected from casework and thus, surfaced sporadically;” in addition to the potential for generating hits, Masson suggested value in studying misses. “Firearms examiners should take advantage of this current expanded database to fully familiarize themselves with the extent of similarities found in many non-identifications in order to hone their criteria for striae identification” because the “examiner’s power of discrimination can be heightened because of the experience.”

Even in the best of operational circumstances, RBIDs should not be expected to produce torrents of hits or completed matches. They are, at root, akin to detecting low-base-rate phenomena in large populations, and present particular difficulties because—by construction—such large populations contain a great many elements that are virtually identical in all but the tiniest details. A major reason that the current state databases have underperformed in generating hits is that they have been undersearched. As

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