Forensic genetic genealogy uses DNA traces to identify criminals by analyzing partial matches in third-party ancestry databases. It involves matching DNA from crime scenes to relatives in databases like GEDmatch, then using genealogists and mathematical algorithms to build family trees and identify suspects.
The algorithm optimizes the process by focusing on potential ancestors of the target, prioritizing matches that are more likely to lead to the criminal. It reduces the workload by avoiding false leads and inefficient tree expansion, solving cases up to 10 times faster than traditional methods.
Ethical issues include privacy violations for individuals whose DNA is collected without consent, especially when law enforcement knocks on doors to request DNA samples. There are also concerns about the long-term storage and potential misuse of genetic data, as well as the broader implications for family members whose DNA is indirectly included in the database.
Genealogists use their expertise in tracing family trees, often relying on geography, ethnicity, and historical records that the algorithm doesn't consider. They act as a complement to the algorithm, helping to resolve complex cases and providing insights that the mathematical model cannot capture.
Third-party databases like GEDmatch and Family Tree DNA provide lists of potential relatives based on DNA matches. These databases are crucial for identifying distant relatives of the suspect, which helps genealogists and algorithms narrow down the family tree to find the perpetrator.
The Golden State Killer case marked the first high-profile use of forensic genetic genealogy to solve a decades-old cold case. It demonstrated the potential of combining DNA analysis with family tree research to identify a previously untraceable suspect, even when the suspect's DNA was not directly in the database.
The algorithm uses a two-stage process: ascending to find ancestors and descending to trace descendants. It prioritizes matches that are more likely to be related to the target, minimizing unnecessary work by avoiding overshooting or undershooting in the tree construction.
The centimorgan value measures the amount of shared DNA between individuals, indicating how closely they are related. It helps in determining the likelihood of a match being a distant relative, which is crucial for building accurate family trees and identifying suspects.
Databases like GEDmatch have transitioned to an opt-in system, where users must consent to allow law enforcement access. This change was prompted by privacy concerns after the Golden State Killer case, but only about 30% of users currently opt in.
The algorithm provides recommendations for which matches to investigate next, based on mathematical optimization. Genealogists then perform the actual research, such as looking up marriage records or birth certificates, and feed the results back into the algorithm to refine the search.
Halloween may be behind us in the US but here at The Future of Everything we’re not quite done with spooky season. If you’re pairing your trick-or-treat haul with some scary movies, we invite you to revisit with us a conversation Russ had with Lawrence Wein) a couple years ago about the work he’s doing in forensic genetic genealogy to crack cold cases. Professor Wein shares how he’s using math to catch criminals through traces of their DNA. It’s both haunting and hopeful, and we hope you’ll take another listen.
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Chapters:
(00:00:00) Introduction
Russ Altman introduces guest Lawrence Wein, professor of management science at Stanford University.
(00:02:18) Forensic Genealogy Explained
Forensic genetic genealogy and its impact on solving unsolved crimes.
(00:04:31) Third-Party Databases in Genealogy
Insight into databases that allow law enforcement to search for criminal suspects.
(00:08:23) Math Models in Genealogy
Using mathematical models to streamline genealogy work.
(00:11:31) Components of the Genealogy Algorithm
The algorithm's methods, including ascending and descending family trees.
(00:14:12) Algorithm Efficiency and Comparison
Comparing the new algorithm's effectiveness to traditional genealogy strategies.
(00:16:53) Algorithm in Practice
Role of human input alongside the mathematical algorithm in genealogy cases.
(00:20:42) Role of Genealogists
Genealogists’ insights on balancing human skill and mathematical algorithms.
(00:22:45) DNA Databases and Ethics
The ethical and privacy concerns related to using genetic data.
(00:27:01) Background and Interest in Forensic Genealogy
Lawrence’s journey from operations management to forensic genealogy.
(00:30:16) Conclusion
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